{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9cadb813",
   "metadata": {},
   "source": [
    "# 中国的资本\n",
    "\n",
    "- 投资完成额 k_total\n",
    "- 投资建筑安装 k_build\n",
    "- 投资设备购置 k_equipment\n",
    "- 投资其他 k_other"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddeef3ca",
   "metadata": {},
   "source": [
    "数据维度：\n",
    "- 结构（总项，建筑安装，设备购置，其他）\n",
    "- 行业（19行业）\n",
    "- 时间（2003-2017，2018至今）\n",
    "- 属性（当期值，同比）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d45c238e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import warnings\n",
    "\n",
    "from utils import calculate_depreciation_rate_multiple_methods\n",
    "\n",
    "warnings.filterwarnings('ignore', category=UserWarning, module='openpyxl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "3a7659bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 装配数据，约束总量为固定资本形成"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "e9e4d9f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "class CapitalStockData:\n",
    "    def __init__(self):\n",
    "        self.ind_name = self.load_ind_names()\n",
    "        self.total_k = self.load_data('固定资本形成总额.xlsx', keep_round=1)\n",
    "        self.total_k_ind = self.load_data('年度固定资产投资完成额-19行业-2003-2017.xlsx', keep_round=1)\n",
    "        self.total_k_ind_yoy = self.load_data('年度固定资产投资完成额-19行业-同比-2004-2024.xlsx', keep_round=1)\n",
    "        self.build_k_ind = self.load_data('年度固定资产投资完成额-建筑安装工程-19行业-2003-2017.xlsx', keep_round=1)\n",
    "        self.build_k_ind_yoy = self.load_data('年度固定资产投资完成额-建筑安装工程-19行业-同比-2018至今.xlsx', keep_round=1)\n",
    "        self.equipment_k_ind = self.load_data('年度固定资产投资完成额-设备工器具购置-19行业-2003-2017.xlsx', keep_round=1)\n",
    "        self.equipment_k_ind_yoy = self.load_data('年度固定资产投资完成额-设备工器具购置-同比-19行业-2018至今.xlsx', keep_round=1)\n",
    "        self.other_k_ind = self.load_data('年度固定资产投资完成额-其他费用-19行业-2003-2017.xlsx', keep_round=1)\n",
    "        self.other_k_ind_yoy = self.load_data('年度固定资产投资完成额-其他费用-同比-2018至今.xlsx', keep_round=1)\n",
    "    \n",
    "    def load_ind_names(self):\n",
    "        ind_name = pd.read_excel('data/kdata/19行业名称.xlsx', index_col=0)\n",
    "        dic1 = dict(zip(ind_name.iloc[:,0].tolist(), ind_name.iloc[:,-1].tolist()))\n",
    "        dic2 = dict(zip(ind_name.iloc[:,1].tolist(), ind_name.iloc[:,-1].tolist()))\n",
    "        return {**dic1, **dic2}\n",
    "    \n",
    "    def load_data(self, path, keep_round=False):\n",
    "        data = pd.read_excel(f'data/kdata/{path}', index_col=0)\n",
    "        data = self.auto_transform_data(data)\n",
    "        if keep_round:\n",
    "            data = data.round(keep_round)\n",
    "        data = self.change_col_name(data)\n",
    "        return data\n",
    "\n",
    "    def change_col_name(self, df):\n",
    "        cols_map = {}\n",
    "        for col in df.columns:\n",
    "            cols_map[col] = col\n",
    "            for c, v in self.ind_name.items():\n",
    "                if c in col:\n",
    "                    cols_map[col] = v\n",
    "                    break \n",
    "        df.columns = [cols_map[col] for col in df.columns]\n",
    "        return df\n",
    "    \n",
    "    @staticmethod\n",
    "    def auto_transform_data(df):\n",
    "        if isinstance(df.index[0],str):\n",
    "            df = df.T\n",
    "        new_idx = []\n",
    "        for s in df.index:\n",
    "            if pd.isna(s):\n",
    "                continue\n",
    "            elif 'Wind' in str(s):\n",
    "                continue\n",
    "            else:\n",
    "                new_idx.append(s)\n",
    "        # print(new_idx)\n",
    "        df = df.loc[new_idx]\n",
    "        df.index = pd.to_datetime(df.index)\n",
    "        df.index.name = None\n",
    "        df.columns.name = None\n",
    "        return df\n",
    "\n",
    "    @staticmethod\n",
    "    def tab_data(a, b):\n",
    "        a_tab = pd.DataFrame(a,index=b.index,columns=b.columns)\n",
    "        a_and_b = pd.concat([a, a_tab])\n",
    "        for year in range(2018, 2025):\n",
    "            location = pd.to_datetime(f'{year}-12-31')\n",
    "            last_year = pd.to_datetime(f'{year-1}-12-31')\n",
    "            a_and_b.loc[location,:] = a_and_b.loc[last_year,:] * (1 + b.loc[location,:] / 100)\n",
    "        return a_and_b.round(1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "53f7eaa0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ind_name\n",
      "total_k\n",
      "total_k_ind\n",
      "total_k_ind_yoy\n",
      "build_k_ind\n",
      "build_k_ind_yoy\n",
      "equipment_k_ind\n",
      "equipment_k_ind_yoy\n",
      "other_k_ind\n",
      "other_k_ind_yoy\n"
     ]
    }
   ],
   "source": [
    "cap = CapitalStockData()\n",
    "\n",
    "for k in cap.__dict__.keys():\n",
    "    print(k)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f24daab",
   "metadata": {},
   "source": [
    "# 查看总项数据\n",
    "cap.total_k"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "f701c5b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>中国:GDP:资本形成总额:固定资本形成总额:支出法</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1952-12-31</th>\n",
       "      <td>78.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1953-12-31</th>\n",
       "      <td>112.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1954-12-31</th>\n",
       "      <td>137.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1955-12-31</th>\n",
       "      <td>142.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1956-12-31</th>\n",
       "      <td>216.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>433086.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>485400.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-31</th>\n",
       "      <td>508826.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>523590.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-12-31</th>\n",
       "      <td>537875.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>73 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            中国:GDP:资本形成总额:固定资本形成总额:支出法\n",
       "1952-12-31                        78.8\n",
       "1953-12-31                       112.6\n",
       "1954-12-31                       137.9\n",
       "1955-12-31                       142.9\n",
       "1956-12-31                       216.8\n",
       "...                                ...\n",
       "2020-12-31                    433086.0\n",
       "2021-12-31                    485400.7\n",
       "2022-12-31                    508826.5\n",
       "2023-12-31                    523590.3\n",
       "2024-12-31                    537875.6\n",
       "\n",
       "[73 rows x 1 columns]"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 分布查看总项与分项数据\n",
    "cap.total_k\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f09afe0a",
   "metadata": {},
   "source": [
    "# 查看建筑安装工程数据\n",
    "cap.total_k_ind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "08054d6b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2003-12-31</th>\n",
       "      <td>309.8</td>\n",
       "      <td>1037.9</td>\n",
       "      <td>4525.4</td>\n",
       "      <td>1958.0</td>\n",
       "      <td>399.1</td>\n",
       "      <td>4188.1</td>\n",
       "      <td>625.2</td>\n",
       "      <td>585.2</td>\n",
       "      <td>230.5</td>\n",
       "      <td>52.0</td>\n",
       "      <td>7568.8</td>\n",
       "      <td>222.0</td>\n",
       "      <td>186.9</td>\n",
       "      <td>2911.3</td>\n",
       "      <td>48.9</td>\n",
       "      <td>1190.4</td>\n",
       "      <td>244.3</td>\n",
       "      <td>339.6</td>\n",
       "      <td>1467.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-12-31</th>\n",
       "      <td>349.3</td>\n",
       "      <td>1403.8</td>\n",
       "      <td>6377.5</td>\n",
       "      <td>2812.9</td>\n",
       "      <td>409.2</td>\n",
       "      <td>5366.6</td>\n",
       "      <td>645.9</td>\n",
       "      <td>804.5</td>\n",
       "      <td>327.5</td>\n",
       "      <td>55.9</td>\n",
       "      <td>10036.2</td>\n",
       "      <td>256.1</td>\n",
       "      <td>199.9</td>\n",
       "      <td>3528.8</td>\n",
       "      <td>67.1</td>\n",
       "      <td>1497.8</td>\n",
       "      <td>1676.0</td>\n",
       "      <td>398.0</td>\n",
       "      <td>1652.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-31</th>\n",
       "      <td>490.5</td>\n",
       "      <td>2040.9</td>\n",
       "      <td>9223.0</td>\n",
       "      <td>3730.2</td>\n",
       "      <td>476.9</td>\n",
       "      <td>6502.9</td>\n",
       "      <td>638.3</td>\n",
       "      <td>1119.8</td>\n",
       "      <td>496.3</td>\n",
       "      <td>65.2</td>\n",
       "      <td>11905.1</td>\n",
       "      <td>329.5</td>\n",
       "      <td>273.1</td>\n",
       "      <td>4455.9</td>\n",
       "      <td>93.6</td>\n",
       "      <td>1614.4</td>\n",
       "      <td>405.3</td>\n",
       "      <td>456.4</td>\n",
       "      <td>1837.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>669.4</td>\n",
       "      <td>2655.3</td>\n",
       "      <td>11915.4</td>\n",
       "      <td>4136.5</td>\n",
       "      <td>568.8</td>\n",
       "      <td>8364.7</td>\n",
       "      <td>708.8</td>\n",
       "      <td>1350.6</td>\n",
       "      <td>684.3</td>\n",
       "      <td>62.4</td>\n",
       "      <td>15089.0</td>\n",
       "      <td>447.4</td>\n",
       "      <td>285.9</td>\n",
       "      <td>5252.3</td>\n",
       "      <td>126.6</td>\n",
       "      <td>1703.1</td>\n",
       "      <td>492.5</td>\n",
       "      <td>604.8</td>\n",
       "      <td>1981.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>882.2</td>\n",
       "      <td>3467.9</td>\n",
       "      <td>16490.3</td>\n",
       "      <td>4537.5</td>\n",
       "      <td>704.8</td>\n",
       "      <td>9193.6</td>\n",
       "      <td>726.0</td>\n",
       "      <td>1746.2</td>\n",
       "      <td>973.9</td>\n",
       "      <td>76.3</td>\n",
       "      <td>19898.8</td>\n",
       "      <td>593.8</td>\n",
       "      <td>323.3</td>\n",
       "      <td>6583.3</td>\n",
       "      <td>168.6</td>\n",
       "      <td>1771.6</td>\n",
       "      <td>555.5</td>\n",
       "      <td>834.7</td>\n",
       "      <td>2067.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>1385.6</td>\n",
       "      <td>4260.6</td>\n",
       "      <td>21541.8</td>\n",
       "      <td>5206.0</td>\n",
       "      <td>802.7</td>\n",
       "      <td>10619.4</td>\n",
       "      <td>913.4</td>\n",
       "      <td>2254.7</td>\n",
       "      <td>1268.7</td>\n",
       "      <td>114.8</td>\n",
       "      <td>25584.0</td>\n",
       "      <td>879.8</td>\n",
       "      <td>454.9</td>\n",
       "      <td>8839.0</td>\n",
       "      <td>208.5</td>\n",
       "      <td>1870.1</td>\n",
       "      <td>720.5</td>\n",
       "      <td>1053.3</td>\n",
       "      <td>2384.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>2096.8</td>\n",
       "      <td>4854.8</td>\n",
       "      <td>27438.8</td>\n",
       "      <td>6703.2</td>\n",
       "      <td>1111.3</td>\n",
       "      <td>16196.9</td>\n",
       "      <td>1152.9</td>\n",
       "      <td>3165.9</td>\n",
       "      <td>1691.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>31472.3</td>\n",
       "      <td>1305.5</td>\n",
       "      <td>679.2</td>\n",
       "      <td>12932.9</td>\n",
       "      <td>336.2</td>\n",
       "      <td>2595.8</td>\n",
       "      <td>1228.5</td>\n",
       "      <td>1543.7</td>\n",
       "      <td>3089.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>2458.1</td>\n",
       "      <td>5668.5</td>\n",
       "      <td>35304.9</td>\n",
       "      <td>7106.4</td>\n",
       "      <td>1624.4</td>\n",
       "      <td>19614.6</td>\n",
       "      <td>1013.2</td>\n",
       "      <td>3526.6</td>\n",
       "      <td>2148.4</td>\n",
       "      <td>261.0</td>\n",
       "      <td>40527.4</td>\n",
       "      <td>1686.9</td>\n",
       "      <td>747.4</td>\n",
       "      <td>16464.8</td>\n",
       "      <td>495.2</td>\n",
       "      <td>3030.8</td>\n",
       "      <td>1406.5</td>\n",
       "      <td>1898.0</td>\n",
       "      <td>3618.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>4571.5</td>\n",
       "      <td>7080.4</td>\n",
       "      <td>51129.1</td>\n",
       "      <td>7650.4</td>\n",
       "      <td>2493.5</td>\n",
       "      <td>20016.8</td>\n",
       "      <td>1114.9</td>\n",
       "      <td>5172.8</td>\n",
       "      <td>2995.8</td>\n",
       "      <td>406.3</td>\n",
       "      <td>55913.8</td>\n",
       "      <td>2358.5</td>\n",
       "      <td>1105.9</td>\n",
       "      <td>19057.5</td>\n",
       "      <td>822.0</td>\n",
       "      <td>3135.8</td>\n",
       "      <td>1748.0</td>\n",
       "      <td>2299.6</td>\n",
       "      <td>4572.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>6087.3</td>\n",
       "      <td>8184.7</td>\n",
       "      <td>63824.5</td>\n",
       "      <td>8833.2</td>\n",
       "      <td>2951.0</td>\n",
       "      <td>21581.0</td>\n",
       "      <td>1441.6</td>\n",
       "      <td>6941.2</td>\n",
       "      <td>3830.6</td>\n",
       "      <td>549.7</td>\n",
       "      <td>69434.8</td>\n",
       "      <td>3397.5</td>\n",
       "      <td>1585.3</td>\n",
       "      <td>23005.3</td>\n",
       "      <td>1200.4</td>\n",
       "      <td>3758.4</td>\n",
       "      <td>1909.2</td>\n",
       "      <td>3180.5</td>\n",
       "      <td>4905.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>8095.0</td>\n",
       "      <td>9530.3</td>\n",
       "      <td>76931.1</td>\n",
       "      <td>10789.3</td>\n",
       "      <td>2718.6</td>\n",
       "      <td>25694.6</td>\n",
       "      <td>1666.8</td>\n",
       "      <td>9207.9</td>\n",
       "      <td>4681.1</td>\n",
       "      <td>879.5</td>\n",
       "      <td>85763.3</td>\n",
       "      <td>4354.7</td>\n",
       "      <td>2033.7</td>\n",
       "      <td>30753.2</td>\n",
       "      <td>1497.7</td>\n",
       "      <td>4479.7</td>\n",
       "      <td>2347.1</td>\n",
       "      <td>3980.9</td>\n",
       "      <td>4929.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>10578.4</td>\n",
       "      <td>9726.1</td>\n",
       "      <td>90603.5</td>\n",
       "      <td>12771.3</td>\n",
       "      <td>3174.7</td>\n",
       "      <td>31311.7</td>\n",
       "      <td>2221.5</td>\n",
       "      <td>11614.3</td>\n",
       "      <td>4959.2</td>\n",
       "      <td>1001.2</td>\n",
       "      <td>95157.7</td>\n",
       "      <td>5736.8</td>\n",
       "      <td>2801.0</td>\n",
       "      <td>38550.0</td>\n",
       "      <td>1766.9</td>\n",
       "      <td>5524.9</td>\n",
       "      <td>2919.0</td>\n",
       "      <td>4760.8</td>\n",
       "      <td>5975.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>14069.2</td>\n",
       "      <td>8845.0</td>\n",
       "      <td>99064.4</td>\n",
       "      <td>15411.1</td>\n",
       "      <td>3829.1</td>\n",
       "      <td>36308.8</td>\n",
       "      <td>3123.8</td>\n",
       "      <td>13797.3</td>\n",
       "      <td>5211.1</td>\n",
       "      <td>989.0</td>\n",
       "      <td>97909.2</td>\n",
       "      <td>7048.8</td>\n",
       "      <td>3233.7</td>\n",
       "      <td>46710.6</td>\n",
       "      <td>2021.8</td>\n",
       "      <td>6396.3</td>\n",
       "      <td>3901.7</td>\n",
       "      <td>5282.9</td>\n",
       "      <td>6574.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>17007.4</td>\n",
       "      <td>6974.7</td>\n",
       "      <td>105773.4</td>\n",
       "      <td>17532.4</td>\n",
       "      <td>3735.7</td>\n",
       "      <td>40302.7</td>\n",
       "      <td>3561.2</td>\n",
       "      <td>13267.1</td>\n",
       "      <td>4826.0</td>\n",
       "      <td>955.6</td>\n",
       "      <td>103884.3</td>\n",
       "      <td>8932.1</td>\n",
       "      <td>3866.5</td>\n",
       "      <td>57092.1</td>\n",
       "      <td>2058.2</td>\n",
       "      <td>7744.4</td>\n",
       "      <td>4852.9</td>\n",
       "      <td>6009.7</td>\n",
       "      <td>6819.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>18973.0</td>\n",
       "      <td>6366.9</td>\n",
       "      <td>109741.5</td>\n",
       "      <td>18278.5</td>\n",
       "      <td>2911.0</td>\n",
       "      <td>46674.0</td>\n",
       "      <td>3848.5</td>\n",
       "      <td>12559.5</td>\n",
       "      <td>5061.2</td>\n",
       "      <td>840.2</td>\n",
       "      <td>103461.3</td>\n",
       "      <td>9668.2</td>\n",
       "      <td>4186.2</td>\n",
       "      <td>68101.6</td>\n",
       "      <td>2077.0</td>\n",
       "      <td>9330.6</td>\n",
       "      <td>5792.2</td>\n",
       "      <td>7026.2</td>\n",
       "      <td>6874.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               农林牧渔      采矿        制造     电热燃水      建筑     交通运输    信息软件  \\\n",
       "2003-12-31    309.8  1037.9    4525.4   1958.0   399.1   4188.1   625.2   \n",
       "2004-12-31    349.3  1403.8    6377.5   2812.9   409.2   5366.6   645.9   \n",
       "2005-12-31    490.5  2040.9    9223.0   3730.2   476.9   6502.9   638.3   \n",
       "2006-12-31    669.4  2655.3   11915.4   4136.5   568.8   8364.7   708.8   \n",
       "2007-12-31    882.2  3467.9   16490.3   4537.5   704.8   9193.6   726.0   \n",
       "2008-12-31   1385.6  4260.6   21541.8   5206.0   802.7  10619.4   913.4   \n",
       "2009-12-31   2096.8  4854.8   27438.8   6703.2  1111.3  16196.9  1152.9   \n",
       "2010-12-31   2458.1  5668.5   35304.9   7106.4  1624.4  19614.6  1013.2   \n",
       "2011-12-31   4571.5  7080.4   51129.1   7650.4  2493.5  20016.8  1114.9   \n",
       "2012-12-31   6087.3  8184.7   63824.5   8833.2  2951.0  21581.0  1441.6   \n",
       "2013-12-31   8095.0  9530.3   76931.1  10789.3  2718.6  25694.6  1666.8   \n",
       "2014-12-31  10578.4  9726.1   90603.5  12771.3  3174.7  31311.7  2221.5   \n",
       "2015-12-31  14069.2  8845.0   99064.4  15411.1  3829.1  36308.8  3123.8   \n",
       "2016-12-31  17007.4  6974.7  105773.4  17532.4  3735.7  40302.7  3561.2   \n",
       "2017-12-31  18973.0  6366.9  109741.5  18278.5  2911.0  46674.0  3848.5   \n",
       "\n",
       "               批发零售    住宿餐饮      金融       房地产    租赁商务    科学研究    水环公设施  \\\n",
       "2003-12-31    585.2   230.5    52.0    7568.8   222.0   186.9   2911.3   \n",
       "2004-12-31    804.5   327.5    55.9   10036.2   256.1   199.9   3528.8   \n",
       "2005-12-31   1119.8   496.3    65.2   11905.1   329.5   273.1   4455.9   \n",
       "2006-12-31   1350.6   684.3    62.4   15089.0   447.4   285.9   5252.3   \n",
       "2007-12-31   1746.2   973.9    76.3   19898.8   593.8   323.3   6583.3   \n",
       "2008-12-31   2254.7  1268.7   114.8   25584.0   879.8   454.9   8839.0   \n",
       "2009-12-31   3165.9  1691.0   185.0   31472.3  1305.5   679.2  12932.9   \n",
       "2010-12-31   3526.6  2148.4   261.0   40527.4  1686.9   747.4  16464.8   \n",
       "2011-12-31   5172.8  2995.8   406.3   55913.8  2358.5  1105.9  19057.5   \n",
       "2012-12-31   6941.2  3830.6   549.7   69434.8  3397.5  1585.3  23005.3   \n",
       "2013-12-31   9207.9  4681.1   879.5   85763.3  4354.7  2033.7  30753.2   \n",
       "2014-12-31  11614.3  4959.2  1001.2   95157.7  5736.8  2801.0  38550.0   \n",
       "2015-12-31  13797.3  5211.1   989.0   97909.2  7048.8  3233.7  46710.6   \n",
       "2016-12-31  13267.1  4826.0   955.6  103884.3  8932.1  3866.5  57092.1   \n",
       "2017-12-31  12559.5  5061.2   840.2  103461.3  9668.2  4186.2  68101.6   \n",
       "\n",
       "              居民服务      教育   卫生与社会     文体娱    公共管理  \n",
       "2003-12-31    48.9  1190.4   244.3   339.6  1467.7  \n",
       "2004-12-31    67.1  1497.8  1676.0   398.0  1652.4  \n",
       "2005-12-31    93.6  1614.4   405.3   456.4  1837.1  \n",
       "2006-12-31   126.6  1703.1   492.5   604.8  1981.5  \n",
       "2007-12-31   168.6  1771.6   555.5   834.7  2067.0  \n",
       "2008-12-31   208.5  1870.1   720.5  1053.3  2384.0  \n",
       "2009-12-31   336.2  2595.8  1228.5  1543.7  3089.5  \n",
       "2010-12-31   495.2  3030.8  1406.5  1898.0  3618.1  \n",
       "2011-12-31   822.0  3135.8  1748.0  2299.6  4572.2  \n",
       "2012-12-31  1200.4  3758.4  1909.2  3180.5  4905.0  \n",
       "2013-12-31  1497.7  4479.7  2347.1  3980.9  4929.6  \n",
       "2014-12-31  1766.9  5524.9  2919.0  4760.8  5975.7  \n",
       "2015-12-31  2021.8  6396.3  3901.7  5282.9  6574.5  \n",
       "2016-12-31  2058.2  7744.4  4852.9  6009.7  6819.9  \n",
       "2017-12-31  2077.0  9330.6  5792.2  7026.2  6874.0  "
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cap.build_k_ind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "0644ea5b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-12-31</th>\n",
       "      <td>13.5</td>\n",
       "      <td>5.2</td>\n",
       "      <td>12.0</td>\n",
       "      <td>-2.6</td>\n",
       "      <td>-13.9</td>\n",
       "      <td>-19.3</td>\n",
       "      <td>5.3</td>\n",
       "      <td>-5.2</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>-2.6</td>\n",
       "      <td>16.7</td>\n",
       "      <td>14.0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>-9.9</td>\n",
       "      <td>10.0</td>\n",
       "      <td>8.2</td>\n",
       "      <td>23.1</td>\n",
       "      <td>-13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>2.2</td>\n",
       "      <td>25.9</td>\n",
       "      <td>3.3</td>\n",
       "      <td>5.8</td>\n",
       "      <td>-86.0</td>\n",
       "      <td>-18.0</td>\n",
       "      <td>5.9</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>9.9</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>7.2</td>\n",
       "      <td>16.5</td>\n",
       "      <td>16.1</td>\n",
       "      <td>5.6</td>\n",
       "      <td>-10.3</td>\n",
       "      <td>18.0</td>\n",
       "      <td>4.9</td>\n",
       "      <td>13.5</td>\n",
       "      <td>-16.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>23.3</td>\n",
       "      <td>-12.2</td>\n",
       "      <td>1.2</td>\n",
       "      <td>16.7</td>\n",
       "      <td>18.1</td>\n",
       "      <td>-21.3</td>\n",
       "      <td>2.6</td>\n",
       "      <td>-3.3</td>\n",
       "      <td>15.4</td>\n",
       "      <td>-18.4</td>\n",
       "      <td>4.6</td>\n",
       "      <td>7.1</td>\n",
       "      <td>3.3</td>\n",
       "      <td>0.7</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>13.4</td>\n",
       "      <td>24.3</td>\n",
       "      <td>2.8</td>\n",
       "      <td>-6.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>17.8</td>\n",
       "      <td>10.1</td>\n",
       "      <td>22.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>4.7</td>\n",
       "      <td>0.2</td>\n",
       "      <td>2.2</td>\n",
       "      <td>9.0</td>\n",
       "      <td>19.2</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>7.5</td>\n",
       "      <td>16.7</td>\n",
       "      <td>17.5</td>\n",
       "      <td>0.4</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>11.7</td>\n",
       "      <td>22.5</td>\n",
       "      <td>5.6</td>\n",
       "      <td>-37.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-31</th>\n",
       "      <td>9.1</td>\n",
       "      <td>17.9</td>\n",
       "      <td>19.3</td>\n",
       "      <td>17.2</td>\n",
       "      <td>-13.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>5.2</td>\n",
       "      <td>10.3</td>\n",
       "      <td>12.0</td>\n",
       "      <td>5.9</td>\n",
       "      <td>-9.0</td>\n",
       "      <td>17.9</td>\n",
       "      <td>25.0</td>\n",
       "      <td>9.5</td>\n",
       "      <td>23.5</td>\n",
       "      <td>4.2</td>\n",
       "      <td>31.5</td>\n",
       "      <td>6.7</td>\n",
       "      <td>50.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>-0.9</td>\n",
       "      <td>9.8</td>\n",
       "      <td>11.5</td>\n",
       "      <td>19.2</td>\n",
       "      <td>39.5</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>5.1</td>\n",
       "      <td>9.5</td>\n",
       "      <td>12.5</td>\n",
       "      <td>3.7</td>\n",
       "      <td>-9.9</td>\n",
       "      <td>13.2</td>\n",
       "      <td>19.7</td>\n",
       "      <td>-0.9</td>\n",
       "      <td>14.3</td>\n",
       "      <td>2.3</td>\n",
       "      <td>-7.4</td>\n",
       "      <td>2.6</td>\n",
       "      <td>-39.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-12-31</th>\n",
       "      <td>17.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>11.8</td>\n",
       "      <td>26.9</td>\n",
       "      <td>-17.3</td>\n",
       "      <td>8.2</td>\n",
       "      <td>4.1</td>\n",
       "      <td>32.7</td>\n",
       "      <td>4.3</td>\n",
       "      <td>-6.6</td>\n",
       "      <td>-10.6</td>\n",
       "      <td>5.0</td>\n",
       "      <td>8.7</td>\n",
       "      <td>3.7</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>-1.8</td>\n",
       "      <td>-10.0</td>\n",
       "      <td>0.7</td>\n",
       "      <td>-13.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            农林牧渔    采矿    制造  电热燃水    建筑  批发零售  交通运输  住宿餐饮  信息软件    金融   房地产  \\\n",
       "2018-12-31  13.5   5.2  12.0  -2.6 -13.9 -19.3   5.3  -5.2  -0.4 -24.0  -2.6   \n",
       "2019-12-31   2.2  25.9   3.3   5.8 -86.0 -18.0   5.9  -0.2   9.9  -0.1   7.2   \n",
       "2020-12-31  23.3 -12.2   1.2  16.7  18.1 -21.3   2.6  -3.3  15.4 -18.4   4.6   \n",
       "2021-12-31  17.8  10.1  22.1   3.5   4.7   0.2   2.2   9.0  19.2  -0.3   7.5   \n",
       "2022-12-31   9.1  17.9  19.3  17.2 -13.0   7.1   5.2  10.3  12.0   5.9  -9.0   \n",
       "2023-12-31  -0.9   9.8  11.5  19.2  39.5  -0.4   5.1   9.5  12.5   3.7  -9.9   \n",
       "2024-12-31  17.0   5.1  11.8  26.9 -17.3   8.2   4.1  32.7   4.3  -6.6 -10.6   \n",
       "\n",
       "            租赁商务  科学研究  水环公设施  居民服务    教育  卫生与社会   文体娱  公共管理  \n",
       "2018-12-31  16.7  14.0    5.4  -9.9  10.0    8.2  23.1 -13.0  \n",
       "2019-12-31  16.5  16.1    5.6 -10.3  18.0    4.9  13.5 -16.8  \n",
       "2020-12-31   7.1   3.3    0.7  -0.1  13.4   24.3   2.8  -6.9  \n",
       "2021-12-31  16.7  17.5    0.4  -6.0  11.7   22.5   5.6 -37.5  \n",
       "2022-12-31  17.9  25.0    9.5  23.5   4.2   31.5   6.7  50.4  \n",
       "2023-12-31  13.2  19.7   -0.9  14.3   2.3   -7.4   2.6 -39.7  \n",
       "2024-12-31   5.0   8.7    3.7  -0.2  -1.8  -10.0   0.7 -13.8  "
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cap.build_k_ind_yoy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb4ef63d",
   "metadata": {},
   "source": [
    "# 查看设备工器具数据\n",
    "cap.equip_k_ind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "d2a863d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2003-12-31</th>\n",
       "      <td>54.3</td>\n",
       "      <td>333.7</td>\n",
       "      <td>5127.0</td>\n",
       "      <td>1223.0</td>\n",
       "      <td>52.4</td>\n",
       "      <td>726.9</td>\n",
       "      <td>956.5</td>\n",
       "      <td>74.5</td>\n",
       "      <td>35.3</td>\n",
       "      <td>26.8</td>\n",
       "      <td>154.6</td>\n",
       "      <td>22.1</td>\n",
       "      <td>44.1</td>\n",
       "      <td>105.8</td>\n",
       "      <td>5.6</td>\n",
       "      <td>79.8</td>\n",
       "      <td>88.0</td>\n",
       "      <td>54.6</td>\n",
       "      <td>135.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-12-31</th>\n",
       "      <td>86.0</td>\n",
       "      <td>520.0</td>\n",
       "      <td>6898.2</td>\n",
       "      <td>1907.8</td>\n",
       "      <td>65.9</td>\n",
       "      <td>877.7</td>\n",
       "      <td>930.3</td>\n",
       "      <td>125.3</td>\n",
       "      <td>54.2</td>\n",
       "      <td>33.0</td>\n",
       "      <td>209.0</td>\n",
       "      <td>36.1</td>\n",
       "      <td>63.2</td>\n",
       "      <td>123.5</td>\n",
       "      <td>28.6</td>\n",
       "      <td>104.6</td>\n",
       "      <td>236.8</td>\n",
       "      <td>66.9</td>\n",
       "      <td>219.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-31</th>\n",
       "      <td>97.3</td>\n",
       "      <td>852.2</td>\n",
       "      <td>9322.8</td>\n",
       "      <td>2562.0</td>\n",
       "      <td>96.7</td>\n",
       "      <td>1163.7</td>\n",
       "      <td>839.0</td>\n",
       "      <td>187.2</td>\n",
       "      <td>77.2</td>\n",
       "      <td>30.1</td>\n",
       "      <td>258.5</td>\n",
       "      <td>45.2</td>\n",
       "      <td>75.7</td>\n",
       "      <td>155.1</td>\n",
       "      <td>20.3</td>\n",
       "      <td>138.7</td>\n",
       "      <td>135.1</td>\n",
       "      <td>79.2</td>\n",
       "      <td>303.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>141.7</td>\n",
       "      <td>1025.2</td>\n",
       "      <td>11946.6</td>\n",
       "      <td>2941.0</td>\n",
       "      <td>149.3</td>\n",
       "      <td>1301.4</td>\n",
       "      <td>976.2</td>\n",
       "      <td>234.9</td>\n",
       "      <td>116.3</td>\n",
       "      <td>44.2</td>\n",
       "      <td>316.2</td>\n",
       "      <td>54.3</td>\n",
       "      <td>105.4</td>\n",
       "      <td>230.8</td>\n",
       "      <td>34.1</td>\n",
       "      <td>165.7</td>\n",
       "      <td>147.8</td>\n",
       "      <td>102.9</td>\n",
       "      <td>363.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>199.7</td>\n",
       "      <td>1292.6</td>\n",
       "      <td>15540.8</td>\n",
       "      <td>3223.9</td>\n",
       "      <td>182.0</td>\n",
       "      <td>1950.8</td>\n",
       "      <td>1004.2</td>\n",
       "      <td>310.2</td>\n",
       "      <td>158.4</td>\n",
       "      <td>60.4</td>\n",
       "      <td>405.8</td>\n",
       "      <td>81.0</td>\n",
       "      <td>121.7</td>\n",
       "      <td>277.4</td>\n",
       "      <td>40.7</td>\n",
       "      <td>182.5</td>\n",
       "      <td>183.2</td>\n",
       "      <td>119.2</td>\n",
       "      <td>360.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>318.4</td>\n",
       "      <td>1888.6</td>\n",
       "      <td>20622.4</td>\n",
       "      <td>3843.3</td>\n",
       "      <td>257.4</td>\n",
       "      <td>2302.5</td>\n",
       "      <td>1105.3</td>\n",
       "      <td>488.3</td>\n",
       "      <td>233.1</td>\n",
       "      <td>100.7</td>\n",
       "      <td>546.2</td>\n",
       "      <td>137.7</td>\n",
       "      <td>167.0</td>\n",
       "      <td>408.0</td>\n",
       "      <td>66.1</td>\n",
       "      <td>230.5</td>\n",
       "      <td>238.9</td>\n",
       "      <td>163.3</td>\n",
       "      <td>454.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>446.3</td>\n",
       "      <td>2426.9</td>\n",
       "      <td>25797.4</td>\n",
       "      <td>4980.6</td>\n",
       "      <td>311.0</td>\n",
       "      <td>2771.9</td>\n",
       "      <td>1278.7</td>\n",
       "      <td>767.5</td>\n",
       "      <td>331.8</td>\n",
       "      <td>114.0</td>\n",
       "      <td>610.4</td>\n",
       "      <td>239.7</td>\n",
       "      <td>248.5</td>\n",
       "      <td>621.6</td>\n",
       "      <td>101.8</td>\n",
       "      <td>276.7</td>\n",
       "      <td>311.2</td>\n",
       "      <td>242.5</td>\n",
       "      <td>455.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>540.7</td>\n",
       "      <td>2886.0</td>\n",
       "      <td>31844.4</td>\n",
       "      <td>5690.6</td>\n",
       "      <td>390.7</td>\n",
       "      <td>3901.0</td>\n",
       "      <td>1211.6</td>\n",
       "      <td>910.0</td>\n",
       "      <td>372.5</td>\n",
       "      <td>133.6</td>\n",
       "      <td>783.1</td>\n",
       "      <td>333.7</td>\n",
       "      <td>303.8</td>\n",
       "      <td>837.7</td>\n",
       "      <td>102.9</td>\n",
       "      <td>301.8</td>\n",
       "      <td>368.7</td>\n",
       "      <td>298.8</td>\n",
       "      <td>480.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>1050.9</td>\n",
       "      <td>3352.9</td>\n",
       "      <td>42368.2</td>\n",
       "      <td>5334.2</td>\n",
       "      <td>435.9</td>\n",
       "      <td>3848.3</td>\n",
       "      <td>922.5</td>\n",
       "      <td>1133.1</td>\n",
       "      <td>431.7</td>\n",
       "      <td>147.7</td>\n",
       "      <td>1168.8</td>\n",
       "      <td>441.2</td>\n",
       "      <td>314.1</td>\n",
       "      <td>1001.1</td>\n",
       "      <td>160.8</td>\n",
       "      <td>290.1</td>\n",
       "      <td>370.8</td>\n",
       "      <td>340.5</td>\n",
       "      <td>467.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>1354.0</td>\n",
       "      <td>3696.8</td>\n",
       "      <td>50299.6</td>\n",
       "      <td>6048.3</td>\n",
       "      <td>464.2</td>\n",
       "      <td>4548.8</td>\n",
       "      <td>1051.2</td>\n",
       "      <td>1501.2</td>\n",
       "      <td>597.6</td>\n",
       "      <td>179.9</td>\n",
       "      <td>1647.7</td>\n",
       "      <td>505.0</td>\n",
       "      <td>538.8</td>\n",
       "      <td>1391.5</td>\n",
       "      <td>258.7</td>\n",
       "      <td>394.5</td>\n",
       "      <td>468.4</td>\n",
       "      <td>460.0</td>\n",
       "      <td>532.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>1760.5</td>\n",
       "      <td>3829.1</td>\n",
       "      <td>59706.3</td>\n",
       "      <td>6845.5</td>\n",
       "      <td>573.7</td>\n",
       "      <td>5124.6</td>\n",
       "      <td>1209.5</td>\n",
       "      <td>1926.9</td>\n",
       "      <td>656.3</td>\n",
       "      <td>212.5</td>\n",
       "      <td>1958.6</td>\n",
       "      <td>676.4</td>\n",
       "      <td>743.0</td>\n",
       "      <td>1844.1</td>\n",
       "      <td>287.1</td>\n",
       "      <td>408.7</td>\n",
       "      <td>561.1</td>\n",
       "      <td>534.8</td>\n",
       "      <td>437.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>2074.6</td>\n",
       "      <td>3552.2</td>\n",
       "      <td>64740.6</td>\n",
       "      <td>8013.5</td>\n",
       "      <td>609.0</td>\n",
       "      <td>5932.4</td>\n",
       "      <td>1677.5</td>\n",
       "      <td>2440.6</td>\n",
       "      <td>643.5</td>\n",
       "      <td>240.8</td>\n",
       "      <td>2107.6</td>\n",
       "      <td>1275.7</td>\n",
       "      <td>1027.2</td>\n",
       "      <td>2186.0</td>\n",
       "      <td>307.2</td>\n",
       "      <td>561.2</td>\n",
       "      <td>767.7</td>\n",
       "      <td>659.7</td>\n",
       "      <td>570.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>2642.0</td>\n",
       "      <td>3062.2</td>\n",
       "      <td>70419.2</td>\n",
       "      <td>9036.8</td>\n",
       "      <td>777.5</td>\n",
       "      <td>6429.4</td>\n",
       "      <td>2091.2</td>\n",
       "      <td>3336.4</td>\n",
       "      <td>705.0</td>\n",
       "      <td>217.3</td>\n",
       "      <td>2036.3</td>\n",
       "      <td>1524.2</td>\n",
       "      <td>1135.7</td>\n",
       "      <td>2695.6</td>\n",
       "      <td>408.1</td>\n",
       "      <td>754.1</td>\n",
       "      <td>864.7</td>\n",
       "      <td>747.8</td>\n",
       "      <td>639.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>2982.1</td>\n",
       "      <td>2388.2</td>\n",
       "      <td>70857.3</td>\n",
       "      <td>9677.7</td>\n",
       "      <td>616.3</td>\n",
       "      <td>5919.8</td>\n",
       "      <td>2359.0</td>\n",
       "      <td>3339.2</td>\n",
       "      <td>623.9</td>\n",
       "      <td>247.7</td>\n",
       "      <td>2385.7</td>\n",
       "      <td>2246.0</td>\n",
       "      <td>1204.9</td>\n",
       "      <td>3373.0</td>\n",
       "      <td>415.8</td>\n",
       "      <td>746.0</td>\n",
       "      <td>963.6</td>\n",
       "      <td>824.8</td>\n",
       "      <td>689.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>3074.8</td>\n",
       "      <td>2012.4</td>\n",
       "      <td>73220.3</td>\n",
       "      <td>9167.5</td>\n",
       "      <td>510.2</td>\n",
       "      <td>6191.7</td>\n",
       "      <td>2651.3</td>\n",
       "      <td>2905.4</td>\n",
       "      <td>615.9</td>\n",
       "      <td>157.4</td>\n",
       "      <td>2418.1</td>\n",
       "      <td>2193.4</td>\n",
       "      <td>1341.2</td>\n",
       "      <td>3892.8</td>\n",
       "      <td>417.0</td>\n",
       "      <td>819.7</td>\n",
       "      <td>1036.1</td>\n",
       "      <td>793.1</td>\n",
       "      <td>639.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              农林牧渔      采矿       制造    电热燃水     建筑    交通运输    信息软件    批发零售  \\\n",
       "2003-12-31    54.3   333.7   5127.0  1223.0   52.4   726.9   956.5    74.5   \n",
       "2004-12-31    86.0   520.0   6898.2  1907.8   65.9   877.7   930.3   125.3   \n",
       "2005-12-31    97.3   852.2   9322.8  2562.0   96.7  1163.7   839.0   187.2   \n",
       "2006-12-31   141.7  1025.2  11946.6  2941.0  149.3  1301.4   976.2   234.9   \n",
       "2007-12-31   199.7  1292.6  15540.8  3223.9  182.0  1950.8  1004.2   310.2   \n",
       "2008-12-31   318.4  1888.6  20622.4  3843.3  257.4  2302.5  1105.3   488.3   \n",
       "2009-12-31   446.3  2426.9  25797.4  4980.6  311.0  2771.9  1278.7   767.5   \n",
       "2010-12-31   540.7  2886.0  31844.4  5690.6  390.7  3901.0  1211.6   910.0   \n",
       "2011-12-31  1050.9  3352.9  42368.2  5334.2  435.9  3848.3   922.5  1133.1   \n",
       "2012-12-31  1354.0  3696.8  50299.6  6048.3  464.2  4548.8  1051.2  1501.2   \n",
       "2013-12-31  1760.5  3829.1  59706.3  6845.5  573.7  5124.6  1209.5  1926.9   \n",
       "2014-12-31  2074.6  3552.2  64740.6  8013.5  609.0  5932.4  1677.5  2440.6   \n",
       "2015-12-31  2642.0  3062.2  70419.2  9036.8  777.5  6429.4  2091.2  3336.4   \n",
       "2016-12-31  2982.1  2388.2  70857.3  9677.7  616.3  5919.8  2359.0  3339.2   \n",
       "2017-12-31  3074.8  2012.4  73220.3  9167.5  510.2  6191.7  2651.3  2905.4   \n",
       "\n",
       "             住宿餐饮     金融     房地产    租赁商务    科学研究   水环公设施   居民服务     教育  \\\n",
       "2003-12-31   35.3   26.8   154.6    22.1    44.1   105.8    5.6   79.8   \n",
       "2004-12-31   54.2   33.0   209.0    36.1    63.2   123.5   28.6  104.6   \n",
       "2005-12-31   77.2   30.1   258.5    45.2    75.7   155.1   20.3  138.7   \n",
       "2006-12-31  116.3   44.2   316.2    54.3   105.4   230.8   34.1  165.7   \n",
       "2007-12-31  158.4   60.4   405.8    81.0   121.7   277.4   40.7  182.5   \n",
       "2008-12-31  233.1  100.7   546.2   137.7   167.0   408.0   66.1  230.5   \n",
       "2009-12-31  331.8  114.0   610.4   239.7   248.5   621.6  101.8  276.7   \n",
       "2010-12-31  372.5  133.6   783.1   333.7   303.8   837.7  102.9  301.8   \n",
       "2011-12-31  431.7  147.7  1168.8   441.2   314.1  1001.1  160.8  290.1   \n",
       "2012-12-31  597.6  179.9  1647.7   505.0   538.8  1391.5  258.7  394.5   \n",
       "2013-12-31  656.3  212.5  1958.6   676.4   743.0  1844.1  287.1  408.7   \n",
       "2014-12-31  643.5  240.8  2107.6  1275.7  1027.2  2186.0  307.2  561.2   \n",
       "2015-12-31  705.0  217.3  2036.3  1524.2  1135.7  2695.6  408.1  754.1   \n",
       "2016-12-31  623.9  247.7  2385.7  2246.0  1204.9  3373.0  415.8  746.0   \n",
       "2017-12-31  615.9  157.4  2418.1  2193.4  1341.2  3892.8  417.0  819.7   \n",
       "\n",
       "             卫生与社会    文体娱   公共管理  \n",
       "2003-12-31    88.0   54.6  135.8  \n",
       "2004-12-31   236.8   66.9  219.6  \n",
       "2005-12-31   135.1   79.2  303.4  \n",
       "2006-12-31   147.8  102.9  363.6  \n",
       "2007-12-31   183.2  119.2  360.2  \n",
       "2008-12-31   238.9  163.3  454.5  \n",
       "2009-12-31   311.2  242.5  455.5  \n",
       "2010-12-31   368.7  298.8  480.8  \n",
       "2011-12-31   370.8  340.5  467.2  \n",
       "2012-12-31   468.4  460.0  532.1  \n",
       "2013-12-31   561.1  534.8  437.8  \n",
       "2014-12-31   767.7  659.7  570.7  \n",
       "2015-12-31   864.7  747.8  639.3  \n",
       "2016-12-31   963.6  824.8  689.0  \n",
       "2017-12-31  1036.1  793.1  639.2  "
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cap.equipment_k_ind"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "469f88c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-12-31</th>\n",
       "      <td>12.9</td>\n",
       "      <td>4.2</td>\n",
       "      <td>6.6</td>\n",
       "      <td>-13.7</td>\n",
       "      <td>-7.8</td>\n",
       "      <td>-29.9</td>\n",
       "      <td>9.4</td>\n",
       "      <td>-7.6</td>\n",
       "      <td>11.6</td>\n",
       "      <td>70.1</td>\n",
       "      <td>-1.1</td>\n",
       "      <td>-15.1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0.7</td>\n",
       "      <td>-24.4</td>\n",
       "      <td>-2.0</td>\n",
       "      <td>8.3</td>\n",
       "      <td>14.5</td>\n",
       "      <td>-35.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>-7.5</td>\n",
       "      <td>16.5</td>\n",
       "      <td>1.0</td>\n",
       "      <td>-3.4</td>\n",
       "      <td>-67.2</td>\n",
       "      <td>-12.8</td>\n",
       "      <td>-17.7</td>\n",
       "      <td>-7.7</td>\n",
       "      <td>5.3</td>\n",
       "      <td>-0.2</td>\n",
       "      <td>6.2</td>\n",
       "      <td>8.7</td>\n",
       "      <td>4.4</td>\n",
       "      <td>-5.4</td>\n",
       "      <td>-5.5</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>9.1</td>\n",
       "      <td>-3.5</td>\n",
       "      <td>-7.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>2.3</td>\n",
       "      <td>-16.9</td>\n",
       "      <td>-8.0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>-28.7</td>\n",
       "      <td>-46.2</td>\n",
       "      <td>-25.9</td>\n",
       "      <td>-42.7</td>\n",
       "      <td>16.0</td>\n",
       "      <td>-46.3</td>\n",
       "      <td>-20.1</td>\n",
       "      <td>-17.7</td>\n",
       "      <td>-3.6</td>\n",
       "      <td>-25.1</td>\n",
       "      <td>-40.6</td>\n",
       "      <td>-16.4</td>\n",
       "      <td>33.1</td>\n",
       "      <td>-16.2</td>\n",
       "      <td>-12.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>-25.7</td>\n",
       "      <td>0.2</td>\n",
       "      <td>1.9</td>\n",
       "      <td>-5.3</td>\n",
       "      <td>15.1</td>\n",
       "      <td>-40.9</td>\n",
       "      <td>0.3</td>\n",
       "      <td>-29.0</td>\n",
       "      <td>11.7</td>\n",
       "      <td>48.5</td>\n",
       "      <td>-13.6</td>\n",
       "      <td>-8.4</td>\n",
       "      <td>4.9</td>\n",
       "      <td>-45.4</td>\n",
       "      <td>-25.5</td>\n",
       "      <td>16.8</td>\n",
       "      <td>9.8</td>\n",
       "      <td>-29.5</td>\n",
       "      <td>-59.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-31</th>\n",
       "      <td>-11.5</td>\n",
       "      <td>17.2</td>\n",
       "      <td>5.3</td>\n",
       "      <td>26.6</td>\n",
       "      <td>58.3</td>\n",
       "      <td>0.4</td>\n",
       "      <td>-5.5</td>\n",
       "      <td>3.4</td>\n",
       "      <td>4.0</td>\n",
       "      <td>8.1</td>\n",
       "      <td>-11.1</td>\n",
       "      <td>-22.2</td>\n",
       "      <td>16.1</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>-4.7</td>\n",
       "      <td>-0.8</td>\n",
       "      <td>9.6</td>\n",
       "      <td>-12.1</td>\n",
       "      <td>-11.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>-6.3</td>\n",
       "      <td>5.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>33.2</td>\n",
       "      <td>-12.6</td>\n",
       "      <td>-3.5</td>\n",
       "      <td>-18.1</td>\n",
       "      <td>39.2</td>\n",
       "      <td>19.2</td>\n",
       "      <td>32.4</td>\n",
       "      <td>-6.7</td>\n",
       "      <td>15.3</td>\n",
       "      <td>10.0</td>\n",
       "      <td>-17.8</td>\n",
       "      <td>-2.1</td>\n",
       "      <td>21.8</td>\n",
       "      <td>15.3</td>\n",
       "      <td>-23.6</td>\n",
       "      <td>-4.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-12-31</th>\n",
       "      <td>-5.5</td>\n",
       "      <td>17.8</td>\n",
       "      <td>6.5</td>\n",
       "      <td>16.5</td>\n",
       "      <td>65.5</td>\n",
       "      <td>20.9</td>\n",
       "      <td>53.5</td>\n",
       "      <td>18.5</td>\n",
       "      <td>20.0</td>\n",
       "      <td>-9.0</td>\n",
       "      <td>-24.5</td>\n",
       "      <td>42.8</td>\n",
       "      <td>35.3</td>\n",
       "      <td>20.0</td>\n",
       "      <td>28.8</td>\n",
       "      <td>16.9</td>\n",
       "      <td>-11.4</td>\n",
       "      <td>7.0</td>\n",
       "      <td>140.4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            农林牧渔    采矿   制造  电热燃水    建筑  批发零售  交通运输  住宿餐饮  信息软件    金融   房地产  \\\n",
       "2018-12-31  12.9   4.2  6.6 -13.7  -7.8 -29.9   9.4  -7.6  11.6  70.1  -1.1   \n",
       "2019-12-31  -7.5  16.5  1.0  -3.4 -67.2 -12.8 -17.7  -7.7   5.3  -0.2   6.2   \n",
       "2020-12-31   2.3 -16.9 -8.0  23.3 -28.7 -46.2 -25.9 -42.7  16.0 -46.3 -20.1   \n",
       "2021-12-31 -25.7   0.2  1.9  -5.3  15.1 -40.9   0.3 -29.0  11.7  48.5 -13.6   \n",
       "2022-12-31 -11.5  17.2  5.3  26.6  58.3   0.4  -5.5   3.4   4.0   8.1 -11.1   \n",
       "2023-12-31  -6.3   5.9  3.0  33.2 -12.6  -3.5 -18.1  39.2  19.2  32.4  -6.7   \n",
       "2024-12-31  -5.5  17.8  6.5  16.5  65.5  20.9  53.5  18.5  20.0  -9.0 -24.5   \n",
       "\n",
       "            租赁商务  科学研究  水环公设施  居民服务    教育  卫生与社会   文体娱   公共管理  \n",
       "2018-12-31 -15.1   0.5    0.7 -24.4  -2.0    8.3  14.5  -35.4  \n",
       "2019-12-31   8.7   4.4   -5.4  -5.5  -0.6    9.1  -3.5   -7.4  \n",
       "2020-12-31 -17.7  -3.6  -25.1 -40.6 -16.4   33.1 -16.2  -12.8  \n",
       "2021-12-31  -8.4   4.9  -45.4 -25.5  16.8    9.8 -29.5  -59.0  \n",
       "2022-12-31 -22.2  16.1   -0.6  -4.7  -0.8    9.6 -12.1  -11.5  \n",
       "2023-12-31  15.3  10.0  -17.8  -2.1  21.8   15.3 -23.6   -4.6  \n",
       "2024-12-31  42.8  35.3   20.0  28.8  16.9  -11.4   7.0  140.4  "
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cap.equipment_k_ind_yoy"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d8414b3",
   "metadata": {},
   "source": [
    "# 2003-2017年设备工器具+建筑安装工程"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "7f52cb14",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2017-12-31 00:00:00 555829.1000000001 350973.2 0.6314408511537088\n",
      "2016,求和为：332804.9,固定资本形成为：312702.5,修正系数0.9396\n",
      "2015,求和为：290272.7,固定资本形成为：292361.9,修正系数1.0072\n",
      "2014,求和为：263255.0,固定资本形成为：284480.9,修正系数1.0806\n",
      "2013,求和为：245147.0,固定资本形成为：266066.6,修正系数1.0853\n",
      "2012,求和为：219045.4,固定资本形成为：240213.2,修正系数1.0966\n",
      "2011,求和为：197699.1,固定资本形成为：215709.1,修正系数1.0911\n",
      "2010,求和为：167966.5,固定资本形成为：182459.8,修正系数1.0863\n",
      "2009,求和为：147679.8,固定资本形成为：153897.0,修正系数1.0421\n",
      "2008,求和为：117652.1,固定资本形成为：125845.3,修正系数1.0696\n",
      "2007,求和为：98790.4,固定资本形成为：103286.2,修正系数1.0455\n",
      "2006,求和为：82273.2,固定资本形成为：85740.7,修正系数1.0421\n",
      "2005,求和为：69252.3,固定资本形成为：74577.3,修正系数1.0769\n",
      "2004,求和为：60111.1,固定资本形成为：64624.6,修正系数1.0751\n",
      "2003,求和为：47895.7,固定资本形成为：53081.4,修正系数1.1083\n"
     ]
    }
   ],
   "source": [
    "# def scale_data(cap:CapitalStockData):\n",
    "    # 建筑安装工程与设备工器具求和\n",
    "new_build = pd.DataFrame(index=cap.build_k_ind.index,columns=cap.build_k_ind.columns)\n",
    "new_equipment = pd.DataFrame(index=cap.equipment_k_ind.index,columns=cap.equipment_k_ind.columns)\n",
    "build_and_equipment_before2018 = cap.build_k_ind + cap.equipment_k_ind\n",
    "\n",
    "year = 2017\n",
    "\n",
    "this_year = pd.to_datetime(f\"{year}-12-31\")\n",
    "bev = build_and_equipment_before2018.loc[this_year].sum()\n",
    "real_v = cap.total_k.loc[this_year].values[0]\n",
    "\n",
    "coef = real_v / bev # 修正系数\n",
    "print(this_year, bev, real_v, coef)\n",
    "new_build.loc[this_year] = coef * cap.build_k_ind.loc[this_year]\n",
    "new_equipment.loc[this_year] = coef * cap.equipment_k_ind.loc[this_year]\n",
    "\n",
    "for year in range(2016, 2002, -1):\n",
    "    this_year = pd.to_datetime(f\"{year}-12-31\")\n",
    "    after_year = this_year + pd.DateOffset(years=1)\n",
    "    \n",
    "    build_se_ratio = cap.build_k_ind.loc[this_year] / cap.build_k_ind.loc[after_year]\n",
    "    equipment_se_ratio = cap.equipment_k_ind.loc[this_year] / cap.equipment_k_ind.loc[after_year]\n",
    "    \n",
    "    build_this_year = new_build.loc[after_year] * build_se_ratio\n",
    "    equipment_this_year = new_equipment.loc[after_year] * equipment_se_ratio\n",
    "    \n",
    "    bev = (build_this_year + equipment_this_year).sum()\n",
    "    real_v = cap.total_k.loc[this_year].values[0]\n",
    "\n",
    "    coef = real_v / bev # 修正系数\n",
    "    \n",
    "    new_build.loc[this_year] = coef * build_this_year\n",
    "    new_equipment.loc[this_year] = coef * equipment_this_year\n",
    "    print(f\"{this_year.year},求和为：{bev:.1f},固定资本形成为：{real_v:.1f},修正系数{coef:.4f}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "dd935111",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_k</th>\n",
       "      <th>build_and_equipment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2003-12-31</th>\n",
       "      <td>53081.4</td>\n",
       "      <td>53081.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-12-31</th>\n",
       "      <td>64624.6</td>\n",
       "      <td>64624.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-31</th>\n",
       "      <td>74577.3</td>\n",
       "      <td>74577.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>85740.7</td>\n",
       "      <td>85740.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>103286.2</td>\n",
       "      <td>103286.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>125845.3</td>\n",
       "      <td>125845.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>153897.0</td>\n",
       "      <td>153897.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>182459.8</td>\n",
       "      <td>182459.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>215709.1</td>\n",
       "      <td>215709.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>240213.2</td>\n",
       "      <td>240213.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>266066.6</td>\n",
       "      <td>266066.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>284480.9</td>\n",
       "      <td>284480.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>292361.9</td>\n",
       "      <td>292361.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>312702.5</td>\n",
       "      <td>312702.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>350973.2</td>\n",
       "      <td>350973.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_k  build_and_equipment\n",
       "2003-12-31   53081.4              53081.4\n",
       "2004-12-31   64624.6              64624.6\n",
       "2005-12-31   74577.3              74577.3\n",
       "2006-12-31   85740.7              85740.7\n",
       "2007-12-31  103286.2             103286.2\n",
       "2008-12-31  125845.3             125845.3\n",
       "2009-12-31  153897.0             153897.0\n",
       "2010-12-31  182459.8             182459.8\n",
       "2011-12-31  215709.1             215709.1\n",
       "2012-12-31  240213.2             240213.2\n",
       "2013-12-31  266066.6             266066.6\n",
       "2014-12-31  284480.9             284480.9\n",
       "2015-12-31  292361.9             292361.9\n",
       "2016-12-31  312702.5             312702.5\n",
       "2017-12-31  350973.2             350973.2"
      ]
     },
     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_build_and_equipment_before2018 = new_build + new_equipment\n",
    "new_build_and_equipment_before2018.index = pd.to_datetime(new_build_and_equipment_before2018.index)\n",
    "df = pd.concat([new_build_and_equipment_before2018.sum(axis=1), cap.total_k], axis=1)\n",
    "df = df.loc[new_build_and_equipment_before2018.index,:]\n",
    "df.columns = ['total_k','build_and_equipment']\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "1f279f86",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>中国:GDP:资本形成总额:固定资本形成总额:支出法</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1952-12-31</th>\n",
       "      <td>78.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1953-12-31</th>\n",
       "      <td>112.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1954-12-31</th>\n",
       "      <td>137.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1955-12-31</th>\n",
       "      <td>142.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1956-12-31</th>\n",
       "      <td>216.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>433086.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>485400.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-31</th>\n",
       "      <td>508826.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>523590.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-12-31</th>\n",
       "      <td>537875.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>73 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            中国:GDP:资本形成总额:固定资本形成总额:支出法\n",
       "1952-12-31                        78.8\n",
       "1953-12-31                       112.6\n",
       "1954-12-31                       137.9\n",
       "1955-12-31                       142.9\n",
       "1956-12-31                       216.8\n",
       "...                                ...\n",
       "2020-12-31                    433086.0\n",
       "2021-12-31                    485400.7\n",
       "2022-12-31                    508826.5\n",
       "2023-12-31                    523590.3\n",
       "2024-12-31                    537875.6\n",
       "\n",
       "[73 rows x 1 columns]"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cap.total_k"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "329b1f3a",
   "metadata": {},
   "source": [
    "# 2018年及以后的数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "e230b1c6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2018年, 固定资产投资完成额: 291500.02, 设备投资完成额: 74315.90 0.9221833264465338\n",
      "2019年, 固定资产投资完成额: 331583.51, 设备投资完成额: 79977.09 0.9684129796828095\n",
      "2020年, 固定资产投资完成额: 355517.85, 设备投资完成额: 76285.18 0.9970376060504891\n",
      "2021年, 固定资产投资完成额: 393170.37, 设备投资完成额: 75295.40 0.9651114308298355\n",
      "2022年, 固定资产投资完成额: 444390.69, 设备投资完成额: 82544.86 1.0355898434473767\n",
      "2023年, 固定资产投资完成额: 445036.45, 设备投资完成额: 84412.83 1.0111900089724715\n",
      "2024年, 固定资产投资完成额: 466430.36, 设备投资完成额: 92073.35 1.038351081931241\n"
     ]
    }
   ],
   "source": [
    "build_2024 = pd.concat(\n",
    "        [   \n",
    "        new_build, \n",
    "        pd.DataFrame(\n",
    "            data=0, \n",
    "            index=cap.build_k_ind_yoy.index, \n",
    "            columns=cap.build_k_ind_yoy.columns\n",
    "            )\n",
    "        ], axis=0)\n",
    "equipment_2024 = pd.concat(\n",
    "        [   \n",
    "        new_equipment, \n",
    "        pd.DataFrame(\n",
    "            data=0, \n",
    "            index=cap.equipment_k_ind_yoy.index, \n",
    "            columns=cap.equipment_k_ind_yoy.columns\n",
    "            )\n",
    "        ], axis=0)\n",
    "\n",
    "for year in range(2018, 2025):\n",
    "    this_year = pd.to_datetime(f\"{year}-12-31\")\n",
    "    last_year = pd.to_datetime(f\"{year-1}-12-31\")\n",
    "    build_v = build_2024.loc[last_year, :] * (1 + cap.build_k_ind_yoy.loc[this_year, :] / 100)\n",
    "    build_v.astype(float)\n",
    "    equipment_v = equipment_2024.loc[last_year, :] * (1 + cap.equipment_k_ind_yoy.loc[this_year, :] / 100)\n",
    "    equipment_v.astype(float)\n",
    "    ratio = ((build_v.sum() + equipment_v.sum()) / cap.total_k.loc[this_year]).values[0]\n",
    "    \n",
    "    build_2024.loc[this_year, :] = build_v / ratio\n",
    "    equipment_2024.loc[this_year, :] = equipment_v / ratio\n",
    "    print(f\"{year}年, 固定资产投资完成额: {build_v.sum():.2f}, 设备投资完成额: {equipment_v.sum():.2f}\", ratio)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "aefe60e3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2003-12-31</th>\n",
       "      <td>439.79091</td>\n",
       "      <td>1473.39892</td>\n",
       "      <td>6424.240746</td>\n",
       "      <td>2779.569404</td>\n",
       "      <td>566.560852</td>\n",
       "      <td>5945.41094</td>\n",
       "      <td>887.531558</td>\n",
       "      <td>830.74771</td>\n",
       "      <td>327.216929</td>\n",
       "      <td>73.819004</td>\n",
       "      <td>10744.63989</td>\n",
       "      <td>315.150361</td>\n",
       "      <td>265.322534</td>\n",
       "      <td>4132.870483</td>\n",
       "      <td>69.418255</td>\n",
       "      <td>1689.887344</td>\n",
       "      <td>346.807357</td>\n",
       "      <td>482.094877</td>\n",
       "      <td>2083.541376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-12-31</th>\n",
       "      <td>447.421867</td>\n",
       "      <td>1798.141474</td>\n",
       "      <td>8169.003599</td>\n",
       "      <td>3603.071772</td>\n",
       "      <td>524.148377</td>\n",
       "      <td>6874.131669</td>\n",
       "      <td>827.339777</td>\n",
       "      <td>1030.492104</td>\n",
       "      <td>419.498029</td>\n",
       "      <td>71.60287</td>\n",
       "      <td>12855.469059</td>\n",
       "      <td>328.041054</td>\n",
       "      <td>256.053911</td>\n",
       "      <td>4520.075249</td>\n",
       "      <td>85.949062</td>\n",
       "      <td>1918.547015</td>\n",
       "      <td>2146.80518</td>\n",
       "      <td>509.802185</td>\n",
       "      <td>2116.575703</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-31</th>\n",
       "      <td>584.405575</td>\n",
       "      <td>2431.627598</td>\n",
       "      <td>10988.731119</td>\n",
       "      <td>4444.341843</td>\n",
       "      <td>568.201873</td>\n",
       "      <td>7747.871581</td>\n",
       "      <td>760.501689</td>\n",
       "      <td>1334.184225</td>\n",
       "      <td>591.315977</td>\n",
       "      <td>77.682454</td>\n",
       "      <td>14184.315607</td>\n",
       "      <td>392.582338</td>\n",
       "      <td>325.384633</td>\n",
       "      <td>5308.976146</td>\n",
       "      <td>111.519596</td>\n",
       "      <td>1923.474739</td>\n",
       "      <td>482.894148</td>\n",
       "      <td>543.777175</td>\n",
       "      <td>2188.810359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>740.608006</td>\n",
       "      <td>2937.759842</td>\n",
       "      <td>13182.911017</td>\n",
       "      <td>4576.523778</td>\n",
       "      <td>629.306594</td>\n",
       "      <td>9254.502223</td>\n",
       "      <td>784.199215</td>\n",
       "      <td>1494.271247</td>\n",
       "      <td>757.093006</td>\n",
       "      <td>69.037854</td>\n",
       "      <td>16694.105471</td>\n",
       "      <td>494.992563</td>\n",
       "      <td>316.312861</td>\n",
       "      <td>5811.017971</td>\n",
       "      <td>140.067185</td>\n",
       "      <td>1884.268741</td>\n",
       "      <td>544.890115</td>\n",
       "      <td>669.136125</td>\n",
       "      <td>2192.283782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>936.571956</td>\n",
       "      <td>3681.634423</td>\n",
       "      <td>17506.634021</td>\n",
       "      <td>4817.15626</td>\n",
       "      <td>748.238398</td>\n",
       "      <td>9760.222102</td>\n",
       "      <td>770.745002</td>\n",
       "      <td>1853.822206</td>\n",
       "      <td>1033.923632</td>\n",
       "      <td>81.002539</td>\n",
       "      <td>21125.207489</td>\n",
       "      <td>630.39722</td>\n",
       "      <td>343.225701</td>\n",
       "      <td>6989.043483</td>\n",
       "      <td>178.991195</td>\n",
       "      <td>1880.787665</td>\n",
       "      <td>589.736706</td>\n",
       "      <td>886.144425</td>\n",
       "      <td>2194.393827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>1406.96861</td>\n",
       "      <td>4326.306624</td>\n",
       "      <td>21874.015876</td>\n",
       "      <td>5286.286506</td>\n",
       "      <td>815.079174</td>\n",
       "      <td>10783.171517</td>\n",
       "      <td>927.48638</td>\n",
       "      <td>2289.471799</td>\n",
       "      <td>1288.265788</td>\n",
       "      <td>116.570436</td>\n",
       "      <td>25978.554353</td>\n",
       "      <td>893.368204</td>\n",
       "      <td>461.915431</td>\n",
       "      <td>8975.314334</td>\n",
       "      <td>211.71547</td>\n",
       "      <td>1898.940529</td>\n",
       "      <td>731.611492</td>\n",
       "      <td>1069.543906</td>\n",
       "      <td>2420.765853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>1990.517978</td>\n",
       "      <td>4608.721232</td>\n",
       "      <td>26047.989649</td>\n",
       "      <td>6363.430041</td>\n",
       "      <td>1054.970731</td>\n",
       "      <td>15375.915986</td>\n",
       "      <td>1094.462122</td>\n",
       "      <td>3005.427731</td>\n",
       "      <td>1605.287057</td>\n",
       "      <td>175.622771</td>\n",
       "      <td>29877.04071</td>\n",
       "      <td>1239.327175</td>\n",
       "      <td>644.772897</td>\n",
       "      <td>12277.36072</td>\n",
       "      <td>319.158787</td>\n",
       "      <td>2464.224803</td>\n",
       "      <td>1166.23013</td>\n",
       "      <td>1465.453359</td>\n",
       "      <td>2932.900273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>2239.234975</td>\n",
       "      <td>5163.786443</td>\n",
       "      <td>32161.412012</td>\n",
       "      <td>6473.658283</td>\n",
       "      <td>1479.766199</td>\n",
       "      <td>17868.149522</td>\n",
       "      <td>922.986403</td>\n",
       "      <td>3212.59756</td>\n",
       "      <td>1957.110134</td>\n",
       "      <td>237.761006</td>\n",
       "      <td>36918.909533</td>\n",
       "      <td>1536.701306</td>\n",
       "      <td>680.852781</td>\n",
       "      <td>14998.802333</td>\n",
       "      <td>451.108238</td>\n",
       "      <td>2760.942745</td>\n",
       "      <td>1281.267643</td>\n",
       "      <td>1729.005322</td>\n",
       "      <td>3295.950556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>3833.666702</td>\n",
       "      <td>5937.633975</td>\n",
       "      <td>42876.939334</td>\n",
       "      <td>6415.636823</td>\n",
       "      <td>2091.05281</td>\n",
       "      <td>16786.118263</td>\n",
       "      <td>934.956799</td>\n",
       "      <td>4337.917777</td>\n",
       "      <td>2512.282337</td>\n",
       "      <td>340.723785</td>\n",
       "      <td>46889.395873</td>\n",
       "      <td>1977.841609</td>\n",
       "      <td>927.409385</td>\n",
       "      <td>15981.647855</td>\n",
       "      <td>689.330423</td>\n",
       "      <td>2629.686546</td>\n",
       "      <td>1465.875401</td>\n",
       "      <td>1928.447982</td>\n",
       "      <td>3834.253723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>4678.608023</td>\n",
       "      <td>6290.638393</td>\n",
       "      <td>49054.559131</td>\n",
       "      <td>6789.065824</td>\n",
       "      <td>2268.094603</td>\n",
       "      <td>16586.834846</td>\n",
       "      <td>1107.992267</td>\n",
       "      <td>5334.902833</td>\n",
       "      <td>2944.142049</td>\n",
       "      <td>422.491224</td>\n",
       "      <td>53366.552066</td>\n",
       "      <td>2611.267846</td>\n",
       "      <td>1218.437945</td>\n",
       "      <td>17681.53059</td>\n",
       "      <td>922.609543</td>\n",
       "      <td>2888.650205</td>\n",
       "      <td>1467.382655</td>\n",
       "      <td>2444.484881</td>\n",
       "      <td>3769.909871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>5673.43393</td>\n",
       "      <td>6679.373364</td>\n",
       "      <td>53917.666835</td>\n",
       "      <td>7561.751785</td>\n",
       "      <td>1905.34867</td>\n",
       "      <td>18008.229211</td>\n",
       "      <td>1168.18773</td>\n",
       "      <td>6453.417206</td>\n",
       "      <td>3280.779688</td>\n",
       "      <td>616.403353</td>\n",
       "      <td>60107.772229</td>\n",
       "      <td>3052.020103</td>\n",
       "      <td>1425.332005</td>\n",
       "      <td>21553.582254</td>\n",
       "      <td>1049.672884</td>\n",
       "      <td>3139.627174</td>\n",
       "      <td>1644.980454</td>\n",
       "      <td>2790.039918</td>\n",
       "      <td>3454.942545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>6831.017293</td>\n",
       "      <td>6280.643319</td>\n",
       "      <td>58507.342819</td>\n",
       "      <td>8247.085679</td>\n",
       "      <td>2050.067175</td>\n",
       "      <td>20219.576133</td>\n",
       "      <td>1434.536879</td>\n",
       "      <td>7499.951235</td>\n",
       "      <td>3202.410663</td>\n",
       "      <td>646.526366</td>\n",
       "      <td>61448.224139</td>\n",
       "      <td>3704.547002</td>\n",
       "      <td>1808.749852</td>\n",
       "      <td>24893.718959</td>\n",
       "      <td>1140.978263</td>\n",
       "      <td>3567.712267</td>\n",
       "      <td>1884.948525</td>\n",
       "      <td>3074.293572</td>\n",
       "      <td>3858.817027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>8407.3353</td>\n",
       "      <td>5285.508823</td>\n",
       "      <td>59197.937841</td>\n",
       "      <td>9209.214812</td>\n",
       "      <td>2288.156228</td>\n",
       "      <td>21697.058534</td>\n",
       "      <td>1866.689933</td>\n",
       "      <td>8244.85595</td>\n",
       "      <td>3113.998307</td>\n",
       "      <td>590.996973</td>\n",
       "      <td>58507.624693</td>\n",
       "      <td>4212.153147</td>\n",
       "      <td>1932.362903</td>\n",
       "      <td>27912.864715</td>\n",
       "      <td>1208.167523</td>\n",
       "      <td>3822.238562</td>\n",
       "      <td>2331.539827</td>\n",
       "      <td>3156.903851</td>\n",
       "      <td>3928.72558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>10090.49033</td>\n",
       "      <td>4138.089473</td>\n",
       "      <td>62755.35766</td>\n",
       "      <td>10401.972827</td>\n",
       "      <td>2216.39079</td>\n",
       "      <td>23911.591697</td>\n",
       "      <td>2112.859941</td>\n",
       "      <td>7871.37036</td>\n",
       "      <td>2863.265774</td>\n",
       "      <td>566.957475</td>\n",
       "      <td>61634.55464</td>\n",
       "      <td>5299.414883</td>\n",
       "      <td>2293.99443</td>\n",
       "      <td>33872.742628</td>\n",
       "      <td>1221.130049</td>\n",
       "      <td>4594.752479</td>\n",
       "      <td>2879.225544</td>\n",
       "      <td>3565.554978</td>\n",
       "      <td>4046.246634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>11980.327269</td>\n",
       "      <td>4020.320755</td>\n",
       "      <td>69295.266167</td>\n",
       "      <td>11541.791598</td>\n",
       "      <td>1838.124318</td>\n",
       "      <td>29471.870287</td>\n",
       "      <td>2430.100116</td>\n",
       "      <td>7930.58137</td>\n",
       "      <td>3195.848436</td>\n",
       "      <td>530.536603</td>\n",
       "      <td>65329.691333</td>\n",
       "      <td>6104.896437</td>\n",
       "      <td>2643.337691</td>\n",
       "      <td>43002.132269</td>\n",
       "      <td>1311.502648</td>\n",
       "      <td>5891.722006</td>\n",
       "      <td>3657.431698</td>\n",
       "      <td>4436.629708</td>\n",
       "      <td>4340.524411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-31</th>\n",
       "      <td>14745.084909</td>\n",
       "      <td>4586.265348</td>\n",
       "      <td>84159.728203</td>\n",
       "      <td>12190.314761</td>\n",
       "      <td>1716.17182</td>\n",
       "      <td>33652.613881</td>\n",
       "      <td>2624.618821</td>\n",
       "      <td>6940.029148</td>\n",
       "      <td>3285.316737</td>\n",
       "      <td>437.231738</td>\n",
       "      <td>69000.50948</td>\n",
       "      <td>7725.594183</td>\n",
       "      <td>3267.685374</td>\n",
       "      <td>49148.84721</td>\n",
       "      <td>1281.376329</td>\n",
       "      <td>7027.77205</td>\n",
       "      <td>4291.273745</td>\n",
       "      <td>5922.348642</td>\n",
       "      <td>4094.908387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>15561.002479</td>\n",
       "      <td>5962.44391</td>\n",
       "      <td>89772.649745</td>\n",
       "      <td>13318.029898</td>\n",
       "      <td>248.10082</td>\n",
       "      <td>36800.537423</td>\n",
       "      <td>2978.539265</td>\n",
       "      <td>5876.443233</td>\n",
       "      <td>3385.689961</td>\n",
       "      <td>451.041565</td>\n",
       "      <td>76381.200701</td>\n",
       "      <td>9293.883304</td>\n",
       "      <td>3917.525682</td>\n",
       "      <td>53594.059294</td>\n",
       "      <td>1186.884719</td>\n",
       "      <td>8563.25885</td>\n",
       "      <td>4648.374457</td>\n",
       "      <td>6941.114844</td>\n",
       "      <td>3518.08975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>19243.723546</td>\n",
       "      <td>5250.580039</td>\n",
       "      <td>91119.854447</td>\n",
       "      <td>15588.319634</td>\n",
       "      <td>293.87765</td>\n",
       "      <td>37869.53588</td>\n",
       "      <td>3447.447008</td>\n",
       "      <td>4638.501895</td>\n",
       "      <td>3283.689775</td>\n",
       "      <td>369.143466</td>\n",
       "      <td>80132.118837</td>\n",
       "      <td>9983.323555</td>\n",
       "      <td>4058.827877</td>\n",
       "      <td>54129.570822</td>\n",
       "      <td>1189.220775</td>\n",
       "      <td>9739.588033</td>\n",
       "      <td>5795.09681</td>\n",
       "      <td>7156.666927</td>\n",
       "      <td>3285.073238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>23488.589621</td>\n",
       "      <td>5989.866495</td>\n",
       "      <td>115279.271104</td>\n",
       "      <td>16717.148203</td>\n",
       "      <td>318.812823</td>\n",
       "      <td>40101.75865</td>\n",
       "      <td>4257.909193</td>\n",
       "      <td>4815.795099</td>\n",
       "      <td>3708.60995</td>\n",
       "      <td>381.340458</td>\n",
       "      <td>89256.043394</td>\n",
       "      <td>12071.703035</td>\n",
       "      <td>4941.52551</td>\n",
       "      <td>56310.688455</td>\n",
       "      <td>1158.278197</td>\n",
       "      <td>11272.397658</td>\n",
       "      <td>7355.620673</td>\n",
       "      <td>7830.640103</td>\n",
       "      <td>2127.392453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-31</th>\n",
       "      <td>24745.367521</td>\n",
       "      <td>6819.352896</td>\n",
       "      <td>132801.776009</td>\n",
       "      <td>18919.167485</td>\n",
       "      <td>267.834952</td>\n",
       "      <td>40737.218858</td>\n",
       "      <td>4604.968198</td>\n",
       "      <td>4980.462664</td>\n",
       "      <td>3950.016313</td>\n",
       "      <td>389.960898</td>\n",
       "      <td>78431.630053</td>\n",
       "      <td>13743.411997</td>\n",
       "      <td>5964.626755</td>\n",
       "      <td>59541.143869</td>\n",
       "      <td>1381.312865</td>\n",
       "      <td>11342.172226</td>\n",
       "      <td>9340.224073</td>\n",
       "      <td>8068.148836</td>\n",
       "      <td>3089.638498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>24251.287093</td>\n",
       "      <td>7404.789815</td>\n",
       "      <td>146435.367178</td>\n",
       "      <td>22302.087087</td>\n",
       "      <td>369.495105</td>\n",
       "      <td>42341.020619</td>\n",
       "      <td>5123.259899</td>\n",
       "      <td>4905.646584</td>\n",
       "      <td>4277.403677</td>\n",
       "      <td>399.914405</td>\n",
       "      <td>69884.886175</td>\n",
       "      <td>15385.379843</td>\n",
       "      <td>7060.649495</td>\n",
       "      <td>58352.310694</td>\n",
       "      <td>1561.368873</td>\n",
       "      <td>11474.640853</td>\n",
       "      <td>8553.335589</td>\n",
       "      <td>8186.315759</td>\n",
       "      <td>1842.435149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-12-31</th>\n",
       "      <td>27326.023339</td>\n",
       "      <td>7494.993005</td>\n",
       "      <td>157668.002041</td>\n",
       "      <td>27256.049525</td>\n",
       "      <td>294.286255</td>\n",
       "      <td>42449.036006</td>\n",
       "      <td>5146.19782</td>\n",
       "      <td>5111.864086</td>\n",
       "      <td>5466.469654</td>\n",
       "      <td>359.724241</td>\n",
       "      <td>60169.521973</td>\n",
       "      <td>15557.983341</td>\n",
       "      <td>7391.455678</td>\n",
       "      <td>58276.383819</td>\n",
       "      <td>1500.692937</td>\n",
       "      <td>10851.914649</td>\n",
       "      <td>7413.679404</td>\n",
       "      <td>7939.145163</td>\n",
       "      <td>1529.520338</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    农林牧渔           采矿             制造          电热燃水  \\\n",
       "2003-12-31     439.79091   1473.39892    6424.240746   2779.569404   \n",
       "2004-12-31    447.421867  1798.141474    8169.003599   3603.071772   \n",
       "2005-12-31    584.405575  2431.627598   10988.731119   4444.341843   \n",
       "2006-12-31    740.608006  2937.759842   13182.911017   4576.523778   \n",
       "2007-12-31    936.571956  3681.634423   17506.634021    4817.15626   \n",
       "2008-12-31    1406.96861  4326.306624   21874.015876   5286.286506   \n",
       "2009-12-31   1990.517978  4608.721232   26047.989649   6363.430041   \n",
       "2010-12-31   2239.234975  5163.786443   32161.412012   6473.658283   \n",
       "2011-12-31   3833.666702  5937.633975   42876.939334   6415.636823   \n",
       "2012-12-31   4678.608023  6290.638393   49054.559131   6789.065824   \n",
       "2013-12-31    5673.43393  6679.373364   53917.666835   7561.751785   \n",
       "2014-12-31   6831.017293  6280.643319   58507.342819   8247.085679   \n",
       "2015-12-31     8407.3353  5285.508823   59197.937841   9209.214812   \n",
       "2016-12-31   10090.49033  4138.089473    62755.35766  10401.972827   \n",
       "2017-12-31  11980.327269  4020.320755   69295.266167  11541.791598   \n",
       "2018-12-31  14745.084909  4586.265348   84159.728203  12190.314761   \n",
       "2019-12-31  15561.002479   5962.44391   89772.649745  13318.029898   \n",
       "2020-12-31  19243.723546  5250.580039   91119.854447  15588.319634   \n",
       "2021-12-31  23488.589621  5989.866495  115279.271104  16717.148203   \n",
       "2022-12-31  24745.367521  6819.352896  132801.776009  18919.167485   \n",
       "2023-12-31  24251.287093  7404.789815  146435.367178  22302.087087   \n",
       "2024-12-31  27326.023339  7494.993005  157668.002041  27256.049525   \n",
       "\n",
       "                     建筑          交通运输         信息软件         批发零售         住宿餐饮  \\\n",
       "2003-12-31   566.560852    5945.41094   887.531558    830.74771   327.216929   \n",
       "2004-12-31   524.148377   6874.131669   827.339777  1030.492104   419.498029   \n",
       "2005-12-31   568.201873   7747.871581   760.501689  1334.184225   591.315977   \n",
       "2006-12-31   629.306594   9254.502223   784.199215  1494.271247   757.093006   \n",
       "2007-12-31   748.238398   9760.222102   770.745002  1853.822206  1033.923632   \n",
       "2008-12-31   815.079174  10783.171517    927.48638  2289.471799  1288.265788   \n",
       "2009-12-31  1054.970731  15375.915986  1094.462122  3005.427731  1605.287057   \n",
       "2010-12-31  1479.766199  17868.149522   922.986403   3212.59756  1957.110134   \n",
       "2011-12-31   2091.05281  16786.118263   934.956799  4337.917777  2512.282337   \n",
       "2012-12-31  2268.094603  16586.834846  1107.992267  5334.902833  2944.142049   \n",
       "2013-12-31   1905.34867  18008.229211   1168.18773  6453.417206  3280.779688   \n",
       "2014-12-31  2050.067175  20219.576133  1434.536879  7499.951235  3202.410663   \n",
       "2015-12-31  2288.156228  21697.058534  1866.689933   8244.85595  3113.998307   \n",
       "2016-12-31   2216.39079  23911.591697  2112.859941   7871.37036  2863.265774   \n",
       "2017-12-31  1838.124318  29471.870287  2430.100116   7930.58137  3195.848436   \n",
       "2018-12-31   1716.17182  33652.613881  2624.618821  6940.029148  3285.316737   \n",
       "2019-12-31    248.10082  36800.537423  2978.539265  5876.443233  3385.689961   \n",
       "2020-12-31    293.87765   37869.53588  3447.447008  4638.501895  3283.689775   \n",
       "2021-12-31   318.812823   40101.75865  4257.909193  4815.795099   3708.60995   \n",
       "2022-12-31   267.834952  40737.218858  4604.968198  4980.462664  3950.016313   \n",
       "2023-12-31   369.495105  42341.020619  5123.259899  4905.646584  4277.403677   \n",
       "2024-12-31   294.286255  42449.036006   5146.19782  5111.864086  5466.469654   \n",
       "\n",
       "                    金融           房地产          租赁商务         科学研究         水环公设施  \\\n",
       "2003-12-31   73.819004   10744.63989    315.150361   265.322534   4132.870483   \n",
       "2004-12-31    71.60287  12855.469059    328.041054   256.053911   4520.075249   \n",
       "2005-12-31   77.682454  14184.315607    392.582338   325.384633   5308.976146   \n",
       "2006-12-31   69.037854  16694.105471    494.992563   316.312861   5811.017971   \n",
       "2007-12-31   81.002539  21125.207489     630.39722   343.225701   6989.043483   \n",
       "2008-12-31  116.570436  25978.554353    893.368204   461.915431   8975.314334   \n",
       "2009-12-31  175.622771   29877.04071   1239.327175   644.772897   12277.36072   \n",
       "2010-12-31  237.761006  36918.909533   1536.701306   680.852781  14998.802333   \n",
       "2011-12-31  340.723785  46889.395873   1977.841609   927.409385  15981.647855   \n",
       "2012-12-31  422.491224  53366.552066   2611.267846  1218.437945   17681.53059   \n",
       "2013-12-31  616.403353  60107.772229   3052.020103  1425.332005  21553.582254   \n",
       "2014-12-31  646.526366  61448.224139   3704.547002  1808.749852  24893.718959   \n",
       "2015-12-31  590.996973  58507.624693   4212.153147  1932.362903  27912.864715   \n",
       "2016-12-31  566.957475   61634.55464   5299.414883   2293.99443  33872.742628   \n",
       "2017-12-31  530.536603  65329.691333   6104.896437  2643.337691  43002.132269   \n",
       "2018-12-31  437.231738   69000.50948   7725.594183  3267.685374   49148.84721   \n",
       "2019-12-31  451.041565  76381.200701   9293.883304  3917.525682  53594.059294   \n",
       "2020-12-31  369.143466  80132.118837   9983.323555  4058.827877  54129.570822   \n",
       "2021-12-31  381.340458  89256.043394  12071.703035   4941.52551  56310.688455   \n",
       "2022-12-31  389.960898  78431.630053  13743.411997  5964.626755  59541.143869   \n",
       "2023-12-31  399.914405  69884.886175  15385.379843  7060.649495  58352.310694   \n",
       "2024-12-31  359.724241  60169.521973  15557.983341  7391.455678  58276.383819   \n",
       "\n",
       "                   居民服务            教育        卫生与社会          文体娱         公共管理  \n",
       "2003-12-31    69.418255   1689.887344   346.807357   482.094877  2083.541376  \n",
       "2004-12-31    85.949062   1918.547015   2146.80518   509.802185  2116.575703  \n",
       "2005-12-31   111.519596   1923.474739   482.894148   543.777175  2188.810359  \n",
       "2006-12-31   140.067185   1884.268741   544.890115   669.136125  2192.283782  \n",
       "2007-12-31   178.991195   1880.787665   589.736706   886.144425  2194.393827  \n",
       "2008-12-31    211.71547   1898.940529   731.611492  1069.543906  2420.765853  \n",
       "2009-12-31   319.158787   2464.224803   1166.23013  1465.453359  2932.900273  \n",
       "2010-12-31   451.108238   2760.942745  1281.267643  1729.005322  3295.950556  \n",
       "2011-12-31   689.330423   2629.686546  1465.875401  1928.447982  3834.253723  \n",
       "2012-12-31   922.609543   2888.650205  1467.382655  2444.484881  3769.909871  \n",
       "2013-12-31  1049.672884   3139.627174  1644.980454  2790.039918  3454.942545  \n",
       "2014-12-31  1140.978263   3567.712267  1884.948525  3074.293572  3858.817027  \n",
       "2015-12-31  1208.167523   3822.238562  2331.539827  3156.903851   3928.72558  \n",
       "2016-12-31  1221.130049   4594.752479  2879.225544  3565.554978  4046.246634  \n",
       "2017-12-31  1311.502648   5891.722006  3657.431698  4436.629708  4340.524411  \n",
       "2018-12-31  1281.376329    7027.77205  4291.273745  5922.348642  4094.908387  \n",
       "2019-12-31  1186.884719    8563.25885  4648.374457  6941.114844   3518.08975  \n",
       "2020-12-31  1189.220775   9739.588033   5795.09681  7156.666927  3285.073238  \n",
       "2021-12-31  1158.278197  11272.397658  7355.620673  7830.640103  2127.392453  \n",
       "2022-12-31  1381.312865  11342.172226  9340.224073  8068.148836  3089.638498  \n",
       "2023-12-31  1561.368873  11474.640853  8553.335589  8186.315759  1842.435149  \n",
       "2024-12-31  1500.692937  10851.914649  7413.679404  7939.145163  1529.520338  "
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_2024"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd348306",
   "metadata": {},
   "source": [
    "# 验证是否一致"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "a4e38c6a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_k</th>\n",
       "      <th>build_and_equipment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2003-12-31</th>\n",
       "      <td>53081.4</td>\n",
       "      <td>53081.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-12-31</th>\n",
       "      <td>64624.6</td>\n",
       "      <td>64624.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-12-31</th>\n",
       "      <td>74577.3</td>\n",
       "      <td>74577.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-12-31</th>\n",
       "      <td>85740.7</td>\n",
       "      <td>85740.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-12-31</th>\n",
       "      <td>103286.2</td>\n",
       "      <td>103286.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>125845.3</td>\n",
       "      <td>125845.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-12-31</th>\n",
       "      <td>153897.0</td>\n",
       "      <td>153897.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-12-31</th>\n",
       "      <td>182459.8</td>\n",
       "      <td>182459.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>215709.1</td>\n",
       "      <td>215709.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>240213.2</td>\n",
       "      <td>240213.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>266066.6</td>\n",
       "      <td>266066.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>284480.9</td>\n",
       "      <td>284480.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>292361.9</td>\n",
       "      <td>292361.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>312702.5</td>\n",
       "      <td>312702.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>350973.2</td>\n",
       "      <td>350973.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-31</th>\n",
       "      <td>396684.6</td>\n",
       "      <td>396684.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>424984.6</td>\n",
       "      <td>424984.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>433086.0</td>\n",
       "      <td>433086.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-12-31</th>\n",
       "      <td>485400.7</td>\n",
       "      <td>485400.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-12-31</th>\n",
       "      <td>508826.5</td>\n",
       "      <td>508826.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>523590.3</td>\n",
       "      <td>523590.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-12-31</th>\n",
       "      <td>537875.6</td>\n",
       "      <td>537875.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             total_k build_and_equipment\n",
       "2003-12-31   53081.4             53081.4\n",
       "2004-12-31   64624.6             64624.6\n",
       "2005-12-31   74577.3             74577.3\n",
       "2006-12-31   85740.7             85740.7\n",
       "2007-12-31  103286.2            103286.2\n",
       "2008-12-31  125845.3            125845.3\n",
       "2009-12-31  153897.0            153897.0\n",
       "2010-12-31  182459.8            182459.8\n",
       "2011-12-31  215709.1            215709.1\n",
       "2012-12-31  240213.2            240213.2\n",
       "2013-12-31  266066.6            266066.6\n",
       "2014-12-31  284480.9            284480.9\n",
       "2015-12-31  292361.9            292361.9\n",
       "2016-12-31  312702.5            312702.5\n",
       "2017-12-31  350973.2            350973.2\n",
       "2018-12-31  396684.6            396684.6\n",
       "2019-12-31  424984.6            424984.6\n",
       "2020-12-31  433086.0            433086.0\n",
       "2021-12-31  485400.7            485400.7\n",
       "2022-12-31  508826.5            508826.5\n",
       "2023-12-31  523590.3            523590.3\n",
       "2024-12-31  537875.6            537875.6"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "be2024 = build_2024 + equipment_2024\n",
    "be2024.index = pd.to_datetime(be2024.index)\n",
    "df_check = pd.concat([ cap.total_k,be2024.sum(axis=1)], axis=1)\n",
    "df_check = df_check.loc[be2024.index,:]\n",
    "df_check.columns = ['total_k','build_and_equipment']\n",
    "df_check\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a377e901",
   "metadata": {},
   "source": [
    "# 最终的建筑安装工程"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "166951d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>439</td>\n",
       "      <td>1473</td>\n",
       "      <td>6424</td>\n",
       "      <td>2779</td>\n",
       "      <td>566</td>\n",
       "      <td>5945</td>\n",
       "      <td>887</td>\n",
       "      <td>830</td>\n",
       "      <td>327</td>\n",
       "      <td>73</td>\n",
       "      <td>10744</td>\n",
       "      <td>315</td>\n",
       "      <td>265</td>\n",
       "      <td>4132</td>\n",
       "      <td>69</td>\n",
       "      <td>1689</td>\n",
       "      <td>346</td>\n",
       "      <td>482</td>\n",
       "      <td>2083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>447</td>\n",
       "      <td>1798</td>\n",
       "      <td>8169</td>\n",
       "      <td>3603</td>\n",
       "      <td>524</td>\n",
       "      <td>6874</td>\n",
       "      <td>827</td>\n",
       "      <td>1030</td>\n",
       "      <td>419</td>\n",
       "      <td>71</td>\n",
       "      <td>12855</td>\n",
       "      <td>328</td>\n",
       "      <td>256</td>\n",
       "      <td>4520</td>\n",
       "      <td>85</td>\n",
       "      <td>1918</td>\n",
       "      <td>2146</td>\n",
       "      <td>509</td>\n",
       "      <td>2116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>584</td>\n",
       "      <td>2431</td>\n",
       "      <td>10988</td>\n",
       "      <td>4444</td>\n",
       "      <td>568</td>\n",
       "      <td>7747</td>\n",
       "      <td>760</td>\n",
       "      <td>1334</td>\n",
       "      <td>591</td>\n",
       "      <td>77</td>\n",
       "      <td>14184</td>\n",
       "      <td>392</td>\n",
       "      <td>325</td>\n",
       "      <td>5308</td>\n",
       "      <td>111</td>\n",
       "      <td>1923</td>\n",
       "      <td>482</td>\n",
       "      <td>543</td>\n",
       "      <td>2188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>740</td>\n",
       "      <td>2937</td>\n",
       "      <td>13182</td>\n",
       "      <td>4576</td>\n",
       "      <td>629</td>\n",
       "      <td>9254</td>\n",
       "      <td>784</td>\n",
       "      <td>1494</td>\n",
       "      <td>757</td>\n",
       "      <td>69</td>\n",
       "      <td>16694</td>\n",
       "      <td>494</td>\n",
       "      <td>316</td>\n",
       "      <td>5811</td>\n",
       "      <td>140</td>\n",
       "      <td>1884</td>\n",
       "      <td>544</td>\n",
       "      <td>669</td>\n",
       "      <td>2192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>936</td>\n",
       "      <td>3681</td>\n",
       "      <td>17506</td>\n",
       "      <td>4817</td>\n",
       "      <td>748</td>\n",
       "      <td>9760</td>\n",
       "      <td>770</td>\n",
       "      <td>1853</td>\n",
       "      <td>1033</td>\n",
       "      <td>81</td>\n",
       "      <td>21125</td>\n",
       "      <td>630</td>\n",
       "      <td>343</td>\n",
       "      <td>6989</td>\n",
       "      <td>178</td>\n",
       "      <td>1880</td>\n",
       "      <td>589</td>\n",
       "      <td>886</td>\n",
       "      <td>2194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>1406</td>\n",
       "      <td>4326</td>\n",
       "      <td>21874</td>\n",
       "      <td>5286</td>\n",
       "      <td>815</td>\n",
       "      <td>10783</td>\n",
       "      <td>927</td>\n",
       "      <td>2289</td>\n",
       "      <td>1288</td>\n",
       "      <td>116</td>\n",
       "      <td>25978</td>\n",
       "      <td>893</td>\n",
       "      <td>461</td>\n",
       "      <td>8975</td>\n",
       "      <td>211</td>\n",
       "      <td>1898</td>\n",
       "      <td>731</td>\n",
       "      <td>1069</td>\n",
       "      <td>2420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>1990</td>\n",
       "      <td>4608</td>\n",
       "      <td>26047</td>\n",
       "      <td>6363</td>\n",
       "      <td>1054</td>\n",
       "      <td>15375</td>\n",
       "      <td>1094</td>\n",
       "      <td>3005</td>\n",
       "      <td>1605</td>\n",
       "      <td>175</td>\n",
       "      <td>29877</td>\n",
       "      <td>1239</td>\n",
       "      <td>644</td>\n",
       "      <td>12277</td>\n",
       "      <td>319</td>\n",
       "      <td>2464</td>\n",
       "      <td>1166</td>\n",
       "      <td>1465</td>\n",
       "      <td>2932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>2239</td>\n",
       "      <td>5163</td>\n",
       "      <td>32161</td>\n",
       "      <td>6473</td>\n",
       "      <td>1479</td>\n",
       "      <td>17868</td>\n",
       "      <td>922</td>\n",
       "      <td>3212</td>\n",
       "      <td>1957</td>\n",
       "      <td>237</td>\n",
       "      <td>36918</td>\n",
       "      <td>1536</td>\n",
       "      <td>680</td>\n",
       "      <td>14998</td>\n",
       "      <td>451</td>\n",
       "      <td>2760</td>\n",
       "      <td>1281</td>\n",
       "      <td>1729</td>\n",
       "      <td>3295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>3833</td>\n",
       "      <td>5937</td>\n",
       "      <td>42876</td>\n",
       "      <td>6415</td>\n",
       "      <td>2091</td>\n",
       "      <td>16786</td>\n",
       "      <td>934</td>\n",
       "      <td>4337</td>\n",
       "      <td>2512</td>\n",
       "      <td>340</td>\n",
       "      <td>46889</td>\n",
       "      <td>1977</td>\n",
       "      <td>927</td>\n",
       "      <td>15981</td>\n",
       "      <td>689</td>\n",
       "      <td>2629</td>\n",
       "      <td>1465</td>\n",
       "      <td>1928</td>\n",
       "      <td>3834</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>4678</td>\n",
       "      <td>6290</td>\n",
       "      <td>49054</td>\n",
       "      <td>6789</td>\n",
       "      <td>2268</td>\n",
       "      <td>16586</td>\n",
       "      <td>1107</td>\n",
       "      <td>5334</td>\n",
       "      <td>2944</td>\n",
       "      <td>422</td>\n",
       "      <td>53366</td>\n",
       "      <td>2611</td>\n",
       "      <td>1218</td>\n",
       "      <td>17681</td>\n",
       "      <td>922</td>\n",
       "      <td>2888</td>\n",
       "      <td>1467</td>\n",
       "      <td>2444</td>\n",
       "      <td>3769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>5673</td>\n",
       "      <td>6679</td>\n",
       "      <td>53917</td>\n",
       "      <td>7561</td>\n",
       "      <td>1905</td>\n",
       "      <td>18008</td>\n",
       "      <td>1168</td>\n",
       "      <td>6453</td>\n",
       "      <td>3280</td>\n",
       "      <td>616</td>\n",
       "      <td>60107</td>\n",
       "      <td>3052</td>\n",
       "      <td>1425</td>\n",
       "      <td>21553</td>\n",
       "      <td>1049</td>\n",
       "      <td>3139</td>\n",
       "      <td>1644</td>\n",
       "      <td>2790</td>\n",
       "      <td>3454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>6831</td>\n",
       "      <td>6280</td>\n",
       "      <td>58507</td>\n",
       "      <td>8247</td>\n",
       "      <td>2050</td>\n",
       "      <td>20219</td>\n",
       "      <td>1434</td>\n",
       "      <td>7499</td>\n",
       "      <td>3202</td>\n",
       "      <td>646</td>\n",
       "      <td>61448</td>\n",
       "      <td>3704</td>\n",
       "      <td>1808</td>\n",
       "      <td>24893</td>\n",
       "      <td>1140</td>\n",
       "      <td>3567</td>\n",
       "      <td>1884</td>\n",
       "      <td>3074</td>\n",
       "      <td>3858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>8407</td>\n",
       "      <td>5285</td>\n",
       "      <td>59197</td>\n",
       "      <td>9209</td>\n",
       "      <td>2288</td>\n",
       "      <td>21697</td>\n",
       "      <td>1866</td>\n",
       "      <td>8244</td>\n",
       "      <td>3113</td>\n",
       "      <td>590</td>\n",
       "      <td>58507</td>\n",
       "      <td>4212</td>\n",
       "      <td>1932</td>\n",
       "      <td>27912</td>\n",
       "      <td>1208</td>\n",
       "      <td>3822</td>\n",
       "      <td>2331</td>\n",
       "      <td>3156</td>\n",
       "      <td>3928</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>10090</td>\n",
       "      <td>4138</td>\n",
       "      <td>62755</td>\n",
       "      <td>10401</td>\n",
       "      <td>2216</td>\n",
       "      <td>23911</td>\n",
       "      <td>2112</td>\n",
       "      <td>7871</td>\n",
       "      <td>2863</td>\n",
       "      <td>566</td>\n",
       "      <td>61634</td>\n",
       "      <td>5299</td>\n",
       "      <td>2293</td>\n",
       "      <td>33872</td>\n",
       "      <td>1221</td>\n",
       "      <td>4594</td>\n",
       "      <td>2879</td>\n",
       "      <td>3565</td>\n",
       "      <td>4046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>11980</td>\n",
       "      <td>4020</td>\n",
       "      <td>69295</td>\n",
       "      <td>11541</td>\n",
       "      <td>1838</td>\n",
       "      <td>29471</td>\n",
       "      <td>2430</td>\n",
       "      <td>7930</td>\n",
       "      <td>3195</td>\n",
       "      <td>530</td>\n",
       "      <td>65329</td>\n",
       "      <td>6104</td>\n",
       "      <td>2643</td>\n",
       "      <td>43002</td>\n",
       "      <td>1311</td>\n",
       "      <td>5891</td>\n",
       "      <td>3657</td>\n",
       "      <td>4436</td>\n",
       "      <td>4340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>14745</td>\n",
       "      <td>4586</td>\n",
       "      <td>84159</td>\n",
       "      <td>12190</td>\n",
       "      <td>1716</td>\n",
       "      <td>33652</td>\n",
       "      <td>2624</td>\n",
       "      <td>6940</td>\n",
       "      <td>3285</td>\n",
       "      <td>437</td>\n",
       "      <td>69000</td>\n",
       "      <td>7725</td>\n",
       "      <td>3267</td>\n",
       "      <td>49148</td>\n",
       "      <td>1281</td>\n",
       "      <td>7027</td>\n",
       "      <td>4291</td>\n",
       "      <td>5922</td>\n",
       "      <td>4094</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>15561</td>\n",
       "      <td>5962</td>\n",
       "      <td>89772</td>\n",
       "      <td>13318</td>\n",
       "      <td>248</td>\n",
       "      <td>36800</td>\n",
       "      <td>2978</td>\n",
       "      <td>5876</td>\n",
       "      <td>3385</td>\n",
       "      <td>451</td>\n",
       "      <td>76381</td>\n",
       "      <td>9293</td>\n",
       "      <td>3917</td>\n",
       "      <td>53594</td>\n",
       "      <td>1186</td>\n",
       "      <td>8563</td>\n",
       "      <td>4648</td>\n",
       "      <td>6941</td>\n",
       "      <td>3518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>19243</td>\n",
       "      <td>5250</td>\n",
       "      <td>91119</td>\n",
       "      <td>15588</td>\n",
       "      <td>293</td>\n",
       "      <td>37869</td>\n",
       "      <td>3447</td>\n",
       "      <td>4638</td>\n",
       "      <td>3283</td>\n",
       "      <td>369</td>\n",
       "      <td>80132</td>\n",
       "      <td>9983</td>\n",
       "      <td>4058</td>\n",
       "      <td>54129</td>\n",
       "      <td>1189</td>\n",
       "      <td>9739</td>\n",
       "      <td>5795</td>\n",
       "      <td>7156</td>\n",
       "      <td>3285</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>23488</td>\n",
       "      <td>5989</td>\n",
       "      <td>115279</td>\n",
       "      <td>16717</td>\n",
       "      <td>318</td>\n",
       "      <td>40101</td>\n",
       "      <td>4257</td>\n",
       "      <td>4815</td>\n",
       "      <td>3708</td>\n",
       "      <td>381</td>\n",
       "      <td>89256</td>\n",
       "      <td>12071</td>\n",
       "      <td>4941</td>\n",
       "      <td>56310</td>\n",
       "      <td>1158</td>\n",
       "      <td>11272</td>\n",
       "      <td>7355</td>\n",
       "      <td>7830</td>\n",
       "      <td>2127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>24745</td>\n",
       "      <td>6819</td>\n",
       "      <td>132801</td>\n",
       "      <td>18919</td>\n",
       "      <td>267</td>\n",
       "      <td>40737</td>\n",
       "      <td>4604</td>\n",
       "      <td>4980</td>\n",
       "      <td>3950</td>\n",
       "      <td>389</td>\n",
       "      <td>78431</td>\n",
       "      <td>13743</td>\n",
       "      <td>5964</td>\n",
       "      <td>59541</td>\n",
       "      <td>1381</td>\n",
       "      <td>11342</td>\n",
       "      <td>9340</td>\n",
       "      <td>8068</td>\n",
       "      <td>3089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>24251</td>\n",
       "      <td>7404</td>\n",
       "      <td>146435</td>\n",
       "      <td>22302</td>\n",
       "      <td>369</td>\n",
       "      <td>42341</td>\n",
       "      <td>5123</td>\n",
       "      <td>4905</td>\n",
       "      <td>4277</td>\n",
       "      <td>399</td>\n",
       "      <td>69884</td>\n",
       "      <td>15385</td>\n",
       "      <td>7060</td>\n",
       "      <td>58352</td>\n",
       "      <td>1561</td>\n",
       "      <td>11474</td>\n",
       "      <td>8553</td>\n",
       "      <td>8186</td>\n",
       "      <td>1842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <td>27326</td>\n",
       "      <td>7494</td>\n",
       "      <td>157668</td>\n",
       "      <td>27256</td>\n",
       "      <td>294</td>\n",
       "      <td>42449</td>\n",
       "      <td>5146</td>\n",
       "      <td>5111</td>\n",
       "      <td>5466</td>\n",
       "      <td>359</td>\n",
       "      <td>60169</td>\n",
       "      <td>15557</td>\n",
       "      <td>7391</td>\n",
       "      <td>58276</td>\n",
       "      <td>1500</td>\n",
       "      <td>10851</td>\n",
       "      <td>7413</td>\n",
       "      <td>7939</td>\n",
       "      <td>1529</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       农林牧渔    采矿      制造   电热燃水    建筑   交通运输  信息软件  批发零售  住宿餐饮   金融    房地产  \\\n",
       "2003    439  1473    6424   2779   566   5945   887   830   327   73  10744   \n",
       "2004    447  1798    8169   3603   524   6874   827  1030   419   71  12855   \n",
       "2005    584  2431   10988   4444   568   7747   760  1334   591   77  14184   \n",
       "2006    740  2937   13182   4576   629   9254   784  1494   757   69  16694   \n",
       "2007    936  3681   17506   4817   748   9760   770  1853  1033   81  21125   \n",
       "2008   1406  4326   21874   5286   815  10783   927  2289  1288  116  25978   \n",
       "2009   1990  4608   26047   6363  1054  15375  1094  3005  1605  175  29877   \n",
       "2010   2239  5163   32161   6473  1479  17868   922  3212  1957  237  36918   \n",
       "2011   3833  5937   42876   6415  2091  16786   934  4337  2512  340  46889   \n",
       "2012   4678  6290   49054   6789  2268  16586  1107  5334  2944  422  53366   \n",
       "2013   5673  6679   53917   7561  1905  18008  1168  6453  3280  616  60107   \n",
       "2014   6831  6280   58507   8247  2050  20219  1434  7499  3202  646  61448   \n",
       "2015   8407  5285   59197   9209  2288  21697  1866  8244  3113  590  58507   \n",
       "2016  10090  4138   62755  10401  2216  23911  2112  7871  2863  566  61634   \n",
       "2017  11980  4020   69295  11541  1838  29471  2430  7930  3195  530  65329   \n",
       "2018  14745  4586   84159  12190  1716  33652  2624  6940  3285  437  69000   \n",
       "2019  15561  5962   89772  13318   248  36800  2978  5876  3385  451  76381   \n",
       "2020  19243  5250   91119  15588   293  37869  3447  4638  3283  369  80132   \n",
       "2021  23488  5989  115279  16717   318  40101  4257  4815  3708  381  89256   \n",
       "2022  24745  6819  132801  18919   267  40737  4604  4980  3950  389  78431   \n",
       "2023  24251  7404  146435  22302   369  42341  5123  4905  4277  399  69884   \n",
       "2024  27326  7494  157668  27256   294  42449  5146  5111  5466  359  60169   \n",
       "\n",
       "       租赁商务  科学研究  水环公设施  居民服务     教育  卫生与社会   文体娱  公共管理  \n",
       "2003    315   265   4132    69   1689    346   482  2083  \n",
       "2004    328   256   4520    85   1918   2146   509  2116  \n",
       "2005    392   325   5308   111   1923    482   543  2188  \n",
       "2006    494   316   5811   140   1884    544   669  2192  \n",
       "2007    630   343   6989   178   1880    589   886  2194  \n",
       "2008    893   461   8975   211   1898    731  1069  2420  \n",
       "2009   1239   644  12277   319   2464   1166  1465  2932  \n",
       "2010   1536   680  14998   451   2760   1281  1729  3295  \n",
       "2011   1977   927  15981   689   2629   1465  1928  3834  \n",
       "2012   2611  1218  17681   922   2888   1467  2444  3769  \n",
       "2013   3052  1425  21553  1049   3139   1644  2790  3454  \n",
       "2014   3704  1808  24893  1140   3567   1884  3074  3858  \n",
       "2015   4212  1932  27912  1208   3822   2331  3156  3928  \n",
       "2016   5299  2293  33872  1221   4594   2879  3565  4046  \n",
       "2017   6104  2643  43002  1311   5891   3657  4436  4340  \n",
       "2018   7725  3267  49148  1281   7027   4291  5922  4094  \n",
       "2019   9293  3917  53594  1186   8563   4648  6941  3518  \n",
       "2020   9983  4058  54129  1189   9739   5795  7156  3285  \n",
       "2021  12071  4941  56310  1158  11272   7355  7830  2127  \n",
       "2022  13743  5964  59541  1381  11342   9340  8068  3089  \n",
       "2023  15385  7060  58352  1561  11474   8553  8186  1842  \n",
       "2024  15557  7391  58276  1500  10851   7413  7939  1529  "
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_2024 = build_2024.astype(int)\n",
    "build_2024.index = [s.year for s in build_2024.index]\n",
    "build_2024\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e08c7a57",
   "metadata": {},
   "source": [
    "# 最终的设备工器具购置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "a0ea2bb0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>77</td>\n",
       "      <td>473</td>\n",
       "      <td>7278</td>\n",
       "      <td>1736</td>\n",
       "      <td>74</td>\n",
       "      <td>1031</td>\n",
       "      <td>1357</td>\n",
       "      <td>105</td>\n",
       "      <td>50</td>\n",
       "      <td>38</td>\n",
       "      <td>219</td>\n",
       "      <td>31</td>\n",
       "      <td>62</td>\n",
       "      <td>150</td>\n",
       "      <td>7</td>\n",
       "      <td>113</td>\n",
       "      <td>124</td>\n",
       "      <td>77</td>\n",
       "      <td>192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>110</td>\n",
       "      <td>666</td>\n",
       "      <td>8835</td>\n",
       "      <td>2443</td>\n",
       "      <td>84</td>\n",
       "      <td>1124</td>\n",
       "      <td>1191</td>\n",
       "      <td>160</td>\n",
       "      <td>69</td>\n",
       "      <td>42</td>\n",
       "      <td>267</td>\n",
       "      <td>46</td>\n",
       "      <td>80</td>\n",
       "      <td>158</td>\n",
       "      <td>36</td>\n",
       "      <td>133</td>\n",
       "      <td>303</td>\n",
       "      <td>85</td>\n",
       "      <td>281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>115</td>\n",
       "      <td>1015</td>\n",
       "      <td>11107</td>\n",
       "      <td>3052</td>\n",
       "      <td>115</td>\n",
       "      <td>1386</td>\n",
       "      <td>999</td>\n",
       "      <td>223</td>\n",
       "      <td>91</td>\n",
       "      <td>35</td>\n",
       "      <td>307</td>\n",
       "      <td>53</td>\n",
       "      <td>90</td>\n",
       "      <td>184</td>\n",
       "      <td>24</td>\n",
       "      <td>165</td>\n",
       "      <td>160</td>\n",
       "      <td>94</td>\n",
       "      <td>361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>156</td>\n",
       "      <td>1134</td>\n",
       "      <td>13217</td>\n",
       "      <td>3253</td>\n",
       "      <td>165</td>\n",
       "      <td>1439</td>\n",
       "      <td>1080</td>\n",
       "      <td>259</td>\n",
       "      <td>128</td>\n",
       "      <td>48</td>\n",
       "      <td>349</td>\n",
       "      <td>60</td>\n",
       "      <td>116</td>\n",
       "      <td>255</td>\n",
       "      <td>37</td>\n",
       "      <td>183</td>\n",
       "      <td>163</td>\n",
       "      <td>113</td>\n",
       "      <td>402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>212</td>\n",
       "      <td>1372</td>\n",
       "      <td>16498</td>\n",
       "      <td>3422</td>\n",
       "      <td>193</td>\n",
       "      <td>2071</td>\n",
       "      <td>1066</td>\n",
       "      <td>329</td>\n",
       "      <td>168</td>\n",
       "      <td>64</td>\n",
       "      <td>430</td>\n",
       "      <td>85</td>\n",
       "      <td>129</td>\n",
       "      <td>294</td>\n",
       "      <td>43</td>\n",
       "      <td>193</td>\n",
       "      <td>194</td>\n",
       "      <td>126</td>\n",
       "      <td>382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>323</td>\n",
       "      <td>1917</td>\n",
       "      <td>20940</td>\n",
       "      <td>3902</td>\n",
       "      <td>261</td>\n",
       "      <td>2338</td>\n",
       "      <td>1122</td>\n",
       "      <td>495</td>\n",
       "      <td>236</td>\n",
       "      <td>102</td>\n",
       "      <td>554</td>\n",
       "      <td>139</td>\n",
       "      <td>169</td>\n",
       "      <td>414</td>\n",
       "      <td>67</td>\n",
       "      <td>234</td>\n",
       "      <td>242</td>\n",
       "      <td>165</td>\n",
       "      <td>461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>423</td>\n",
       "      <td>2303</td>\n",
       "      <td>24489</td>\n",
       "      <td>4728</td>\n",
       "      <td>295</td>\n",
       "      <td>2631</td>\n",
       "      <td>1213</td>\n",
       "      <td>728</td>\n",
       "      <td>314</td>\n",
       "      <td>108</td>\n",
       "      <td>579</td>\n",
       "      <td>227</td>\n",
       "      <td>235</td>\n",
       "      <td>590</td>\n",
       "      <td>96</td>\n",
       "      <td>262</td>\n",
       "      <td>295</td>\n",
       "      <td>230</td>\n",
       "      <td>432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>492</td>\n",
       "      <td>2629</td>\n",
       "      <td>29009</td>\n",
       "      <td>5183</td>\n",
       "      <td>355</td>\n",
       "      <td>3553</td>\n",
       "      <td>1103</td>\n",
       "      <td>828</td>\n",
       "      <td>339</td>\n",
       "      <td>121</td>\n",
       "      <td>713</td>\n",
       "      <td>303</td>\n",
       "      <td>276</td>\n",
       "      <td>763</td>\n",
       "      <td>93</td>\n",
       "      <td>274</td>\n",
       "      <td>335</td>\n",
       "      <td>272</td>\n",
       "      <td>437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>881</td>\n",
       "      <td>2811</td>\n",
       "      <td>35530</td>\n",
       "      <td>4473</td>\n",
       "      <td>365</td>\n",
       "      <td>3227</td>\n",
       "      <td>773</td>\n",
       "      <td>950</td>\n",
       "      <td>362</td>\n",
       "      <td>123</td>\n",
       "      <td>980</td>\n",
       "      <td>369</td>\n",
       "      <td>263</td>\n",
       "      <td>839</td>\n",
       "      <td>134</td>\n",
       "      <td>243</td>\n",
       "      <td>310</td>\n",
       "      <td>285</td>\n",
       "      <td>391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>1040</td>\n",
       "      <td>2841</td>\n",
       "      <td>38659</td>\n",
       "      <td>4648</td>\n",
       "      <td>356</td>\n",
       "      <td>3496</td>\n",
       "      <td>807</td>\n",
       "      <td>1153</td>\n",
       "      <td>459</td>\n",
       "      <td>138</td>\n",
       "      <td>1266</td>\n",
       "      <td>388</td>\n",
       "      <td>414</td>\n",
       "      <td>1069</td>\n",
       "      <td>198</td>\n",
       "      <td>303</td>\n",
       "      <td>360</td>\n",
       "      <td>353</td>\n",
       "      <td>408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>1233</td>\n",
       "      <td>2683</td>\n",
       "      <td>41845</td>\n",
       "      <td>4797</td>\n",
       "      <td>402</td>\n",
       "      <td>3591</td>\n",
       "      <td>847</td>\n",
       "      <td>1350</td>\n",
       "      <td>459</td>\n",
       "      <td>148</td>\n",
       "      <td>1372</td>\n",
       "      <td>474</td>\n",
       "      <td>520</td>\n",
       "      <td>1292</td>\n",
       "      <td>201</td>\n",
       "      <td>286</td>\n",
       "      <td>393</td>\n",
       "      <td>374</td>\n",
       "      <td>306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>1339</td>\n",
       "      <td>2293</td>\n",
       "      <td>41806</td>\n",
       "      <td>5174</td>\n",
       "      <td>393</td>\n",
       "      <td>3830</td>\n",
       "      <td>1083</td>\n",
       "      <td>1576</td>\n",
       "      <td>415</td>\n",
       "      <td>155</td>\n",
       "      <td>1360</td>\n",
       "      <td>823</td>\n",
       "      <td>663</td>\n",
       "      <td>1411</td>\n",
       "      <td>198</td>\n",
       "      <td>362</td>\n",
       "      <td>495</td>\n",
       "      <td>426</td>\n",
       "      <td>368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>1578</td>\n",
       "      <td>1829</td>\n",
       "      <td>42080</td>\n",
       "      <td>5400</td>\n",
       "      <td>464</td>\n",
       "      <td>3842</td>\n",
       "      <td>1249</td>\n",
       "      <td>1993</td>\n",
       "      <td>421</td>\n",
       "      <td>129</td>\n",
       "      <td>1216</td>\n",
       "      <td>910</td>\n",
       "      <td>678</td>\n",
       "      <td>1610</td>\n",
       "      <td>243</td>\n",
       "      <td>450</td>\n",
       "      <td>516</td>\n",
       "      <td>446</td>\n",
       "      <td>382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>1769</td>\n",
       "      <td>1416</td>\n",
       "      <td>42039</td>\n",
       "      <td>5741</td>\n",
       "      <td>365</td>\n",
       "      <td>3512</td>\n",
       "      <td>1399</td>\n",
       "      <td>1981</td>\n",
       "      <td>370</td>\n",
       "      <td>146</td>\n",
       "      <td>1415</td>\n",
       "      <td>1332</td>\n",
       "      <td>714</td>\n",
       "      <td>2001</td>\n",
       "      <td>246</td>\n",
       "      <td>442</td>\n",
       "      <td>571</td>\n",
       "      <td>489</td>\n",
       "      <td>408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>1941</td>\n",
       "      <td>1270</td>\n",
       "      <td>46234</td>\n",
       "      <td>5788</td>\n",
       "      <td>322</td>\n",
       "      <td>3909</td>\n",
       "      <td>1674</td>\n",
       "      <td>1834</td>\n",
       "      <td>388</td>\n",
       "      <td>99</td>\n",
       "      <td>1526</td>\n",
       "      <td>1385</td>\n",
       "      <td>846</td>\n",
       "      <td>2458</td>\n",
       "      <td>263</td>\n",
       "      <td>517</td>\n",
       "      <td>654</td>\n",
       "      <td>500</td>\n",
       "      <td>403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>2376</td>\n",
       "      <td>1435</td>\n",
       "      <td>53444</td>\n",
       "      <td>5417</td>\n",
       "      <td>322</td>\n",
       "      <td>4638</td>\n",
       "      <td>2025</td>\n",
       "      <td>1394</td>\n",
       "      <td>389</td>\n",
       "      <td>183</td>\n",
       "      <td>1637</td>\n",
       "      <td>1275</td>\n",
       "      <td>922</td>\n",
       "      <td>2684</td>\n",
       "      <td>215</td>\n",
       "      <td>550</td>\n",
       "      <td>768</td>\n",
       "      <td>621</td>\n",
       "      <td>282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>2270</td>\n",
       "      <td>1727</td>\n",
       "      <td>55739</td>\n",
       "      <td>5403</td>\n",
       "      <td>109</td>\n",
       "      <td>3941</td>\n",
       "      <td>2202</td>\n",
       "      <td>1255</td>\n",
       "      <td>371</td>\n",
       "      <td>188</td>\n",
       "      <td>1795</td>\n",
       "      <td>1431</td>\n",
       "      <td>994</td>\n",
       "      <td>2622</td>\n",
       "      <td>210</td>\n",
       "      <td>564</td>\n",
       "      <td>865</td>\n",
       "      <td>619</td>\n",
       "      <td>270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>2329</td>\n",
       "      <td>1439</td>\n",
       "      <td>51432</td>\n",
       "      <td>6682</td>\n",
       "      <td>78</td>\n",
       "      <td>2929</td>\n",
       "      <td>2563</td>\n",
       "      <td>677</td>\n",
       "      <td>213</td>\n",
       "      <td>101</td>\n",
       "      <td>1439</td>\n",
       "      <td>1181</td>\n",
       "      <td>962</td>\n",
       "      <td>1969</td>\n",
       "      <td>125</td>\n",
       "      <td>473</td>\n",
       "      <td>1155</td>\n",
       "      <td>520</td>\n",
       "      <td>236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>1793</td>\n",
       "      <td>1494</td>\n",
       "      <td>54304</td>\n",
       "      <td>6557</td>\n",
       "      <td>93</td>\n",
       "      <td>3044</td>\n",
       "      <td>2966</td>\n",
       "      <td>414</td>\n",
       "      <td>157</td>\n",
       "      <td>156</td>\n",
       "      <td>1288</td>\n",
       "      <td>1121</td>\n",
       "      <td>1045</td>\n",
       "      <td>1114</td>\n",
       "      <td>96</td>\n",
       "      <td>572</td>\n",
       "      <td>1314</td>\n",
       "      <td>380</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>1532</td>\n",
       "      <td>1691</td>\n",
       "      <td>55217</td>\n",
       "      <td>8016</td>\n",
       "      <td>142</td>\n",
       "      <td>2778</td>\n",
       "      <td>2979</td>\n",
       "      <td>402</td>\n",
       "      <td>156</td>\n",
       "      <td>163</td>\n",
       "      <td>1105</td>\n",
       "      <td>842</td>\n",
       "      <td>1172</td>\n",
       "      <td>1069</td>\n",
       "      <td>89</td>\n",
       "      <td>548</td>\n",
       "      <td>1391</td>\n",
       "      <td>322</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>1420</td>\n",
       "      <td>1771</td>\n",
       "      <td>56244</td>\n",
       "      <td>10559</td>\n",
       "      <td>122</td>\n",
       "      <td>2250</td>\n",
       "      <td>3511</td>\n",
       "      <td>383</td>\n",
       "      <td>215</td>\n",
       "      <td>213</td>\n",
       "      <td>1020</td>\n",
       "      <td>960</td>\n",
       "      <td>1275</td>\n",
       "      <td>869</td>\n",
       "      <td>86</td>\n",
       "      <td>661</td>\n",
       "      <td>1586</td>\n",
       "      <td>243</td>\n",
       "      <td>80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <td>1292</td>\n",
       "      <td>2009</td>\n",
       "      <td>57688</td>\n",
       "      <td>11847</td>\n",
       "      <td>195</td>\n",
       "      <td>3326</td>\n",
       "      <td>4058</td>\n",
       "      <td>446</td>\n",
       "      <td>246</td>\n",
       "      <td>187</td>\n",
       "      <td>741</td>\n",
       "      <td>1320</td>\n",
       "      <td>1661</td>\n",
       "      <td>1004</td>\n",
       "      <td>107</td>\n",
       "      <td>744</td>\n",
       "      <td>1353</td>\n",
       "      <td>251</td>\n",
       "      <td>187</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      农林牧渔    采矿     制造   电热燃水   建筑  交通运输  信息软件  批发零售  住宿餐饮   金融   房地产  租赁商务  \\\n",
       "2003    77   473   7278   1736   74  1031  1357   105    50   38   219    31   \n",
       "2004   110   666   8835   2443   84  1124  1191   160    69   42   267    46   \n",
       "2005   115  1015  11107   3052  115  1386   999   223    91   35   307    53   \n",
       "2006   156  1134  13217   3253  165  1439  1080   259   128   48   349    60   \n",
       "2007   212  1372  16498   3422  193  2071  1066   329   168   64   430    85   \n",
       "2008   323  1917  20940   3902  261  2338  1122   495   236  102   554   139   \n",
       "2009   423  2303  24489   4728  295  2631  1213   728   314  108   579   227   \n",
       "2010   492  2629  29009   5183  355  3553  1103   828   339  121   713   303   \n",
       "2011   881  2811  35530   4473  365  3227   773   950   362  123   980   369   \n",
       "2012  1040  2841  38659   4648  356  3496   807  1153   459  138  1266   388   \n",
       "2013  1233  2683  41845   4797  402  3591   847  1350   459  148  1372   474   \n",
       "2014  1339  2293  41806   5174  393  3830  1083  1576   415  155  1360   823   \n",
       "2015  1578  1829  42080   5400  464  3842  1249  1993   421  129  1216   910   \n",
       "2016  1769  1416  42039   5741  365  3512  1399  1981   370  146  1415  1332   \n",
       "2017  1941  1270  46234   5788  322  3909  1674  1834   388   99  1526  1385   \n",
       "2018  2376  1435  53444   5417  322  4638  2025  1394   389  183  1637  1275   \n",
       "2019  2270  1727  55739   5403  109  3941  2202  1255   371  188  1795  1431   \n",
       "2020  2329  1439  51432   6682   78  2929  2563   677   213  101  1439  1181   \n",
       "2021  1793  1494  54304   6557   93  3044  2966   414   157  156  1288  1121   \n",
       "2022  1532  1691  55217   8016  142  2778  2979   402   156  163  1105   842   \n",
       "2023  1420  1771  56244  10559  122  2250  3511   383   215  213  1020   960   \n",
       "2024  1292  2009  57688  11847  195  3326  4058   446   246  187   741  1320   \n",
       "\n",
       "      科学研究  水环公设施  居民服务   教育  卫生与社会  文体娱  公共管理  \n",
       "2003    62    150     7  113    124   77   192  \n",
       "2004    80    158    36  133    303   85   281  \n",
       "2005    90    184    24  165    160   94   361  \n",
       "2006   116    255    37  183    163  113   402  \n",
       "2007   129    294    43  193    194  126   382  \n",
       "2008   169    414    67  234    242  165   461  \n",
       "2009   235    590    96  262    295  230   432  \n",
       "2010   276    763    93  274    335  272   437  \n",
       "2011   263    839   134  243    310  285   391  \n",
       "2012   414   1069   198  303    360  353   408  \n",
       "2013   520   1292   201  286    393  374   306  \n",
       "2014   663   1411   198  362    495  426   368  \n",
       "2015   678   1610   243  450    516  446   382  \n",
       "2016   714   2001   246  442    571  489   408  \n",
       "2017   846   2458   263  517    654  500   403  \n",
       "2018   922   2684   215  550    768  621   282  \n",
       "2019   994   2622   210  564    865  619   270  \n",
       "2020   962   1969   125  473   1155  520   236  \n",
       "2021  1045   1114    96  572   1314  380   100  \n",
       "2022  1172   1069    89  548   1391  322    85  \n",
       "2023  1275    869    86  661   1586  243    80  \n",
       "2024  1661   1004   107  744   1353  251   187  "
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "equipment_2024 = equipment_2024.astype(int)\n",
    "equipment_2024.index = [s.year for s in equipment_2024.index]\n",
    "equipment_2024\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "6919a4f3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>516</td>\n",
       "      <td>1946</td>\n",
       "      <td>13702</td>\n",
       "      <td>4515</td>\n",
       "      <td>640</td>\n",
       "      <td>6976</td>\n",
       "      <td>2244</td>\n",
       "      <td>935</td>\n",
       "      <td>377</td>\n",
       "      <td>111</td>\n",
       "      <td>10963</td>\n",
       "      <td>346</td>\n",
       "      <td>327</td>\n",
       "      <td>4282</td>\n",
       "      <td>76</td>\n",
       "      <td>1802</td>\n",
       "      <td>470</td>\n",
       "      <td>559</td>\n",
       "      <td>2275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>557</td>\n",
       "      <td>2464</td>\n",
       "      <td>17004</td>\n",
       "      <td>6046</td>\n",
       "      <td>608</td>\n",
       "      <td>7998</td>\n",
       "      <td>2018</td>\n",
       "      <td>1190</td>\n",
       "      <td>488</td>\n",
       "      <td>113</td>\n",
       "      <td>13122</td>\n",
       "      <td>374</td>\n",
       "      <td>336</td>\n",
       "      <td>4678</td>\n",
       "      <td>121</td>\n",
       "      <td>2051</td>\n",
       "      <td>2449</td>\n",
       "      <td>594</td>\n",
       "      <td>2397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>699</td>\n",
       "      <td>3446</td>\n",
       "      <td>22095</td>\n",
       "      <td>7496</td>\n",
       "      <td>683</td>\n",
       "      <td>9133</td>\n",
       "      <td>1759</td>\n",
       "      <td>1557</td>\n",
       "      <td>682</td>\n",
       "      <td>112</td>\n",
       "      <td>14491</td>\n",
       "      <td>445</td>\n",
       "      <td>415</td>\n",
       "      <td>5492</td>\n",
       "      <td>135</td>\n",
       "      <td>2088</td>\n",
       "      <td>642</td>\n",
       "      <td>637</td>\n",
       "      <td>2549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>896</td>\n",
       "      <td>4071</td>\n",
       "      <td>26399</td>\n",
       "      <td>7829</td>\n",
       "      <td>794</td>\n",
       "      <td>10693</td>\n",
       "      <td>1864</td>\n",
       "      <td>1753</td>\n",
       "      <td>885</td>\n",
       "      <td>117</td>\n",
       "      <td>17043</td>\n",
       "      <td>554</td>\n",
       "      <td>432</td>\n",
       "      <td>6066</td>\n",
       "      <td>177</td>\n",
       "      <td>2067</td>\n",
       "      <td>707</td>\n",
       "      <td>782</td>\n",
       "      <td>2594</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>1148</td>\n",
       "      <td>5053</td>\n",
       "      <td>34004</td>\n",
       "      <td>8239</td>\n",
       "      <td>941</td>\n",
       "      <td>11831</td>\n",
       "      <td>1836</td>\n",
       "      <td>2182</td>\n",
       "      <td>1201</td>\n",
       "      <td>145</td>\n",
       "      <td>21555</td>\n",
       "      <td>715</td>\n",
       "      <td>472</td>\n",
       "      <td>7283</td>\n",
       "      <td>221</td>\n",
       "      <td>2073</td>\n",
       "      <td>783</td>\n",
       "      <td>1012</td>\n",
       "      <td>2576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>1729</td>\n",
       "      <td>6243</td>\n",
       "      <td>42814</td>\n",
       "      <td>9188</td>\n",
       "      <td>1076</td>\n",
       "      <td>13121</td>\n",
       "      <td>2049</td>\n",
       "      <td>2784</td>\n",
       "      <td>1524</td>\n",
       "      <td>218</td>\n",
       "      <td>26532</td>\n",
       "      <td>1032</td>\n",
       "      <td>630</td>\n",
       "      <td>9389</td>\n",
       "      <td>278</td>\n",
       "      <td>2132</td>\n",
       "      <td>973</td>\n",
       "      <td>1234</td>\n",
       "      <td>2881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>2413</td>\n",
       "      <td>6911</td>\n",
       "      <td>50536</td>\n",
       "      <td>11091</td>\n",
       "      <td>1349</td>\n",
       "      <td>18006</td>\n",
       "      <td>2307</td>\n",
       "      <td>3733</td>\n",
       "      <td>1919</td>\n",
       "      <td>283</td>\n",
       "      <td>30456</td>\n",
       "      <td>1466</td>\n",
       "      <td>879</td>\n",
       "      <td>12867</td>\n",
       "      <td>415</td>\n",
       "      <td>2726</td>\n",
       "      <td>1461</td>\n",
       "      <td>1695</td>\n",
       "      <td>3364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>2731</td>\n",
       "      <td>7792</td>\n",
       "      <td>61170</td>\n",
       "      <td>11656</td>\n",
       "      <td>1834</td>\n",
       "      <td>21421</td>\n",
       "      <td>2025</td>\n",
       "      <td>4040</td>\n",
       "      <td>2296</td>\n",
       "      <td>358</td>\n",
       "      <td>37631</td>\n",
       "      <td>1839</td>\n",
       "      <td>956</td>\n",
       "      <td>15761</td>\n",
       "      <td>544</td>\n",
       "      <td>3034</td>\n",
       "      <td>1616</td>\n",
       "      <td>2001</td>\n",
       "      <td>3732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>4714</td>\n",
       "      <td>8748</td>\n",
       "      <td>78406</td>\n",
       "      <td>10888</td>\n",
       "      <td>2456</td>\n",
       "      <td>20013</td>\n",
       "      <td>1707</td>\n",
       "      <td>5287</td>\n",
       "      <td>2874</td>\n",
       "      <td>463</td>\n",
       "      <td>47869</td>\n",
       "      <td>2346</td>\n",
       "      <td>1190</td>\n",
       "      <td>16820</td>\n",
       "      <td>823</td>\n",
       "      <td>2872</td>\n",
       "      <td>1775</td>\n",
       "      <td>2213</td>\n",
       "      <td>4225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>5718</td>\n",
       "      <td>9131</td>\n",
       "      <td>87713</td>\n",
       "      <td>11437</td>\n",
       "      <td>2624</td>\n",
       "      <td>20082</td>\n",
       "      <td>1914</td>\n",
       "      <td>6487</td>\n",
       "      <td>3403</td>\n",
       "      <td>560</td>\n",
       "      <td>54632</td>\n",
       "      <td>2999</td>\n",
       "      <td>1632</td>\n",
       "      <td>18750</td>\n",
       "      <td>1120</td>\n",
       "      <td>3191</td>\n",
       "      <td>1827</td>\n",
       "      <td>2797</td>\n",
       "      <td>4177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>6906</td>\n",
       "      <td>9362</td>\n",
       "      <td>95762</td>\n",
       "      <td>12358</td>\n",
       "      <td>2307</td>\n",
       "      <td>21599</td>\n",
       "      <td>2015</td>\n",
       "      <td>7803</td>\n",
       "      <td>3739</td>\n",
       "      <td>764</td>\n",
       "      <td>61479</td>\n",
       "      <td>3526</td>\n",
       "      <td>1945</td>\n",
       "      <td>22845</td>\n",
       "      <td>1250</td>\n",
       "      <td>3425</td>\n",
       "      <td>2037</td>\n",
       "      <td>3164</td>\n",
       "      <td>3760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>8170</td>\n",
       "      <td>8573</td>\n",
       "      <td>100313</td>\n",
       "      <td>13421</td>\n",
       "      <td>2443</td>\n",
       "      <td>24049</td>\n",
       "      <td>2517</td>\n",
       "      <td>9075</td>\n",
       "      <td>3617</td>\n",
       "      <td>801</td>\n",
       "      <td>62808</td>\n",
       "      <td>4527</td>\n",
       "      <td>2471</td>\n",
       "      <td>26304</td>\n",
       "      <td>1338</td>\n",
       "      <td>3929</td>\n",
       "      <td>2379</td>\n",
       "      <td>3500</td>\n",
       "      <td>4226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>9985</td>\n",
       "      <td>7114</td>\n",
       "      <td>101277</td>\n",
       "      <td>14609</td>\n",
       "      <td>2752</td>\n",
       "      <td>25539</td>\n",
       "      <td>3115</td>\n",
       "      <td>10237</td>\n",
       "      <td>3534</td>\n",
       "      <td>719</td>\n",
       "      <td>59723</td>\n",
       "      <td>5122</td>\n",
       "      <td>2610</td>\n",
       "      <td>29522</td>\n",
       "      <td>1451</td>\n",
       "      <td>4272</td>\n",
       "      <td>2847</td>\n",
       "      <td>3602</td>\n",
       "      <td>4310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>11859</td>\n",
       "      <td>5554</td>\n",
       "      <td>104794</td>\n",
       "      <td>16142</td>\n",
       "      <td>2581</td>\n",
       "      <td>27423</td>\n",
       "      <td>3511</td>\n",
       "      <td>9852</td>\n",
       "      <td>3233</td>\n",
       "      <td>712</td>\n",
       "      <td>63049</td>\n",
       "      <td>6631</td>\n",
       "      <td>3007</td>\n",
       "      <td>35873</td>\n",
       "      <td>1467</td>\n",
       "      <td>5036</td>\n",
       "      <td>3450</td>\n",
       "      <td>4054</td>\n",
       "      <td>4454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>13921</td>\n",
       "      <td>5290</td>\n",
       "      <td>115529</td>\n",
       "      <td>17329</td>\n",
       "      <td>2160</td>\n",
       "      <td>33380</td>\n",
       "      <td>4104</td>\n",
       "      <td>9764</td>\n",
       "      <td>3583</td>\n",
       "      <td>629</td>\n",
       "      <td>66855</td>\n",
       "      <td>7489</td>\n",
       "      <td>3489</td>\n",
       "      <td>45460</td>\n",
       "      <td>1574</td>\n",
       "      <td>6408</td>\n",
       "      <td>4311</td>\n",
       "      <td>4936</td>\n",
       "      <td>4743</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>17121</td>\n",
       "      <td>6021</td>\n",
       "      <td>137603</td>\n",
       "      <td>17607</td>\n",
       "      <td>2038</td>\n",
       "      <td>38290</td>\n",
       "      <td>4649</td>\n",
       "      <td>8334</td>\n",
       "      <td>3674</td>\n",
       "      <td>620</td>\n",
       "      <td>70637</td>\n",
       "      <td>9000</td>\n",
       "      <td>4189</td>\n",
       "      <td>51832</td>\n",
       "      <td>1496</td>\n",
       "      <td>7577</td>\n",
       "      <td>5059</td>\n",
       "      <td>6543</td>\n",
       "      <td>4376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>17831</td>\n",
       "      <td>7689</td>\n",
       "      <td>145511</td>\n",
       "      <td>18721</td>\n",
       "      <td>357</td>\n",
       "      <td>40741</td>\n",
       "      <td>5180</td>\n",
       "      <td>7131</td>\n",
       "      <td>3756</td>\n",
       "      <td>639</td>\n",
       "      <td>78176</td>\n",
       "      <td>10724</td>\n",
       "      <td>4911</td>\n",
       "      <td>56216</td>\n",
       "      <td>1396</td>\n",
       "      <td>9127</td>\n",
       "      <td>5513</td>\n",
       "      <td>7560</td>\n",
       "      <td>3788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>21572</td>\n",
       "      <td>6689</td>\n",
       "      <td>142551</td>\n",
       "      <td>22270</td>\n",
       "      <td>371</td>\n",
       "      <td>40798</td>\n",
       "      <td>6010</td>\n",
       "      <td>5315</td>\n",
       "      <td>3496</td>\n",
       "      <td>470</td>\n",
       "      <td>81571</td>\n",
       "      <td>11164</td>\n",
       "      <td>5020</td>\n",
       "      <td>56098</td>\n",
       "      <td>1314</td>\n",
       "      <td>10212</td>\n",
       "      <td>6950</td>\n",
       "      <td>7676</td>\n",
       "      <td>3521</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>25281</td>\n",
       "      <td>7483</td>\n",
       "      <td>169583</td>\n",
       "      <td>23274</td>\n",
       "      <td>411</td>\n",
       "      <td>43145</td>\n",
       "      <td>7223</td>\n",
       "      <td>5229</td>\n",
       "      <td>3865</td>\n",
       "      <td>537</td>\n",
       "      <td>90544</td>\n",
       "      <td>13192</td>\n",
       "      <td>5986</td>\n",
       "      <td>57424</td>\n",
       "      <td>1254</td>\n",
       "      <td>11844</td>\n",
       "      <td>8669</td>\n",
       "      <td>8210</td>\n",
       "      <td>2227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>26277</td>\n",
       "      <td>8510</td>\n",
       "      <td>188018</td>\n",
       "      <td>26935</td>\n",
       "      <td>409</td>\n",
       "      <td>43515</td>\n",
       "      <td>7583</td>\n",
       "      <td>5382</td>\n",
       "      <td>4106</td>\n",
       "      <td>552</td>\n",
       "      <td>79536</td>\n",
       "      <td>14585</td>\n",
       "      <td>7136</td>\n",
       "      <td>60610</td>\n",
       "      <td>1470</td>\n",
       "      <td>11890</td>\n",
       "      <td>10731</td>\n",
       "      <td>8390</td>\n",
       "      <td>3174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>25671</td>\n",
       "      <td>9175</td>\n",
       "      <td>202679</td>\n",
       "      <td>32861</td>\n",
       "      <td>491</td>\n",
       "      <td>44591</td>\n",
       "      <td>8634</td>\n",
       "      <td>5288</td>\n",
       "      <td>4492</td>\n",
       "      <td>612</td>\n",
       "      <td>70904</td>\n",
       "      <td>16345</td>\n",
       "      <td>8335</td>\n",
       "      <td>59221</td>\n",
       "      <td>1647</td>\n",
       "      <td>12135</td>\n",
       "      <td>10139</td>\n",
       "      <td>8429</td>\n",
       "      <td>1922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <td>28618</td>\n",
       "      <td>9503</td>\n",
       "      <td>215356</td>\n",
       "      <td>39103</td>\n",
       "      <td>489</td>\n",
       "      <td>45775</td>\n",
       "      <td>9204</td>\n",
       "      <td>5557</td>\n",
       "      <td>5712</td>\n",
       "      <td>546</td>\n",
       "      <td>60910</td>\n",
       "      <td>16877</td>\n",
       "      <td>9052</td>\n",
       "      <td>59280</td>\n",
       "      <td>1607</td>\n",
       "      <td>11595</td>\n",
       "      <td>8766</td>\n",
       "      <td>8190</td>\n",
       "      <td>1716</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       农林牧渔    采矿      制造   电热燃水    建筑   交通运输  信息软件   批发零售  住宿餐饮   金融    房地产  \\\n",
       "2003    516  1946   13702   4515   640   6976  2244    935   377  111  10963   \n",
       "2004    557  2464   17004   6046   608   7998  2018   1190   488  113  13122   \n",
       "2005    699  3446   22095   7496   683   9133  1759   1557   682  112  14491   \n",
       "2006    896  4071   26399   7829   794  10693  1864   1753   885  117  17043   \n",
       "2007   1148  5053   34004   8239   941  11831  1836   2182  1201  145  21555   \n",
       "2008   1729  6243   42814   9188  1076  13121  2049   2784  1524  218  26532   \n",
       "2009   2413  6911   50536  11091  1349  18006  2307   3733  1919  283  30456   \n",
       "2010   2731  7792   61170  11656  1834  21421  2025   4040  2296  358  37631   \n",
       "2011   4714  8748   78406  10888  2456  20013  1707   5287  2874  463  47869   \n",
       "2012   5718  9131   87713  11437  2624  20082  1914   6487  3403  560  54632   \n",
       "2013   6906  9362   95762  12358  2307  21599  2015   7803  3739  764  61479   \n",
       "2014   8170  8573  100313  13421  2443  24049  2517   9075  3617  801  62808   \n",
       "2015   9985  7114  101277  14609  2752  25539  3115  10237  3534  719  59723   \n",
       "2016  11859  5554  104794  16142  2581  27423  3511   9852  3233  712  63049   \n",
       "2017  13921  5290  115529  17329  2160  33380  4104   9764  3583  629  66855   \n",
       "2018  17121  6021  137603  17607  2038  38290  4649   8334  3674  620  70637   \n",
       "2019  17831  7689  145511  18721   357  40741  5180   7131  3756  639  78176   \n",
       "2020  21572  6689  142551  22270   371  40798  6010   5315  3496  470  81571   \n",
       "2021  25281  7483  169583  23274   411  43145  7223   5229  3865  537  90544   \n",
       "2022  26277  8510  188018  26935   409  43515  7583   5382  4106  552  79536   \n",
       "2023  25671  9175  202679  32861   491  44591  8634   5288  4492  612  70904   \n",
       "2024  28618  9503  215356  39103   489  45775  9204   5557  5712  546  60910   \n",
       "\n",
       "       租赁商务  科学研究  水环公设施  居民服务     教育  卫生与社会   文体娱  公共管理  \n",
       "2003    346   327   4282    76   1802    470   559  2275  \n",
       "2004    374   336   4678   121   2051   2449   594  2397  \n",
       "2005    445   415   5492   135   2088    642   637  2549  \n",
       "2006    554   432   6066   177   2067    707   782  2594  \n",
       "2007    715   472   7283   221   2073    783  1012  2576  \n",
       "2008   1032   630   9389   278   2132    973  1234  2881  \n",
       "2009   1466   879  12867   415   2726   1461  1695  3364  \n",
       "2010   1839   956  15761   544   3034   1616  2001  3732  \n",
       "2011   2346  1190  16820   823   2872   1775  2213  4225  \n",
       "2012   2999  1632  18750  1120   3191   1827  2797  4177  \n",
       "2013   3526  1945  22845  1250   3425   2037  3164  3760  \n",
       "2014   4527  2471  26304  1338   3929   2379  3500  4226  \n",
       "2015   5122  2610  29522  1451   4272   2847  3602  4310  \n",
       "2016   6631  3007  35873  1467   5036   3450  4054  4454  \n",
       "2017   7489  3489  45460  1574   6408   4311  4936  4743  \n",
       "2018   9000  4189  51832  1496   7577   5059  6543  4376  \n",
       "2019  10724  4911  56216  1396   9127   5513  7560  3788  \n",
       "2020  11164  5020  56098  1314  10212   6950  7676  3521  \n",
       "2021  13192  5986  57424  1254  11844   8669  8210  2227  \n",
       "2022  14585  7136  60610  1470  11890  10731  8390  3174  \n",
       "2023  16345  8335  59221  1647  12135  10139  8429  1922  \n",
       "2024  16877  9052  59280  1607  11595   8766  8190  1716  "
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_2024 = build_2024 + equipment_2024\n",
    "total_2024\n",
    "# 保存\n",
    "# total_2024.to_excel('data/total_2024.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "a197807b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>13.771</td>\n",
       "      <td>78.175</td>\n",
       "      <td>171.906</td>\n",
       "      <td>93.600</td>\n",
       "      <td>16.934</td>\n",
       "      <td>120.744</td>\n",
       "      <td>17.265</td>\n",
       "      <td>28.650</td>\n",
       "      <td>3.776</td>\n",
       "      <td>5.488</td>\n",
       "      <td>47.970</td>\n",
       "      <td>0.523</td>\n",
       "      <td>16.026</td>\n",
       "      <td>56.281</td>\n",
       "      <td>39.316</td>\n",
       "      <td>51.314</td>\n",
       "      <td>13.121</td>\n",
       "      <td>13.946</td>\n",
       "      <td>38.202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>14.003</td>\n",
       "      <td>90.114</td>\n",
       "      <td>195.522</td>\n",
       "      <td>124.206</td>\n",
       "      <td>15.135</td>\n",
       "      <td>117.599</td>\n",
       "      <td>16.894</td>\n",
       "      <td>28.536</td>\n",
       "      <td>3.873</td>\n",
       "      <td>7.010</td>\n",
       "      <td>42.939</td>\n",
       "      <td>0.554</td>\n",
       "      <td>16.007</td>\n",
       "      <td>60.152</td>\n",
       "      <td>50.912</td>\n",
       "      <td>54.143</td>\n",
       "      <td>13.653</td>\n",
       "      <td>14.649</td>\n",
       "      <td>39.283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987</th>\n",
       "      <td>14.151</td>\n",
       "      <td>101.142</td>\n",
       "      <td>217.242</td>\n",
       "      <td>153.066</td>\n",
       "      <td>13.315</td>\n",
       "      <td>113.915</td>\n",
       "      <td>16.443</td>\n",
       "      <td>28.270</td>\n",
       "      <td>3.945</td>\n",
       "      <td>8.441</td>\n",
       "      <td>37.847</td>\n",
       "      <td>0.581</td>\n",
       "      <td>15.901</td>\n",
       "      <td>63.558</td>\n",
       "      <td>61.825</td>\n",
       "      <td>56.576</td>\n",
       "      <td>14.091</td>\n",
       "      <td>15.247</td>\n",
       "      <td>40.109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>14.444</td>\n",
       "      <td>112.914</td>\n",
       "      <td>240.615</td>\n",
       "      <td>182.694</td>\n",
       "      <td>11.689</td>\n",
       "      <td>111.539</td>\n",
       "      <td>16.178</td>\n",
       "      <td>28.309</td>\n",
       "      <td>4.056</td>\n",
       "      <td>9.919</td>\n",
       "      <td>33.302</td>\n",
       "      <td>0.613</td>\n",
       "      <td>15.965</td>\n",
       "      <td>67.534</td>\n",
       "      <td>73.071</td>\n",
       "      <td>59.533</td>\n",
       "      <td>14.665</td>\n",
       "      <td>15.988</td>\n",
       "      <td>41.334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>14.623</td>\n",
       "      <td>123.554</td>\n",
       "      <td>261.621</td>\n",
       "      <td>210.218</td>\n",
       "      <td>10.019</td>\n",
       "      <td>108.407</td>\n",
       "      <td>15.801</td>\n",
       "      <td>28.140</td>\n",
       "      <td>4.135</td>\n",
       "      <td>11.285</td>\n",
       "      <td>28.630</td>\n",
       "      <td>0.640</td>\n",
       "      <td>15.911</td>\n",
       "      <td>70.912</td>\n",
       "      <td>83.490</td>\n",
       "      <td>61.978</td>\n",
       "      <td>15.117</td>\n",
       "      <td>16.592</td>\n",
       "      <td>42.225</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>18.528</td>\n",
       "      <td>142.699</td>\n",
       "      <td>266.396</td>\n",
       "      <td>255.169</td>\n",
       "      <td>7.259</td>\n",
       "      <td>129.596</td>\n",
       "      <td>18.542</td>\n",
       "      <td>25.355</td>\n",
       "      <td>3.694</td>\n",
       "      <td>10.523</td>\n",
       "      <td>10.488</td>\n",
       "      <td>0.567</td>\n",
       "      <td>14.665</td>\n",
       "      <td>71.661</td>\n",
       "      <td>73.060</td>\n",
       "      <td>61.006</td>\n",
       "      <td>18.154</td>\n",
       "      <td>17.439</td>\n",
       "      <td>43.303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991</th>\n",
       "      <td>23.930</td>\n",
       "      <td>174.012</td>\n",
       "      <td>341.831</td>\n",
       "      <td>304.627</td>\n",
       "      <td>9.011</td>\n",
       "      <td>214.283</td>\n",
       "      <td>30.451</td>\n",
       "      <td>42.604</td>\n",
       "      <td>5.759</td>\n",
       "      <td>13.446</td>\n",
       "      <td>19.947</td>\n",
       "      <td>0.820</td>\n",
       "      <td>16.542</td>\n",
       "      <td>100.010</td>\n",
       "      <td>43.564</td>\n",
       "      <td>72.865</td>\n",
       "      <td>17.326</td>\n",
       "      <td>19.409</td>\n",
       "      <td>62.758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992</th>\n",
       "      <td>32.153</td>\n",
       "      <td>224.076</td>\n",
       "      <td>442.882</td>\n",
       "      <td>410.714</td>\n",
       "      <td>17.181</td>\n",
       "      <td>297.826</td>\n",
       "      <td>42.762</td>\n",
       "      <td>94.215</td>\n",
       "      <td>11.317</td>\n",
       "      <td>23.803</td>\n",
       "      <td>41.679</td>\n",
       "      <td>1.390</td>\n",
       "      <td>23.322</td>\n",
       "      <td>156.721</td>\n",
       "      <td>154.850</td>\n",
       "      <td>95.438</td>\n",
       "      <td>24.844</td>\n",
       "      <td>26.468</td>\n",
       "      <td>104.677</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>35.609</td>\n",
       "      <td>270.665</td>\n",
       "      <td>681.454</td>\n",
       "      <td>592.155</td>\n",
       "      <td>88.614</td>\n",
       "      <td>611.545</td>\n",
       "      <td>87.779</td>\n",
       "      <td>146.398</td>\n",
       "      <td>19.860</td>\n",
       "      <td>51.364</td>\n",
       "      <td>108.553</td>\n",
       "      <td>2.838</td>\n",
       "      <td>37.481</td>\n",
       "      <td>275.841</td>\n",
       "      <td>102.410</td>\n",
       "      <td>134.415</td>\n",
       "      <td>37.652</td>\n",
       "      <td>39.012</td>\n",
       "      <td>232.236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>42.360</td>\n",
       "      <td>294.402</td>\n",
       "      <td>907.591</td>\n",
       "      <td>858.687</td>\n",
       "      <td>103.233</td>\n",
       "      <td>902.296</td>\n",
       "      <td>128.837</td>\n",
       "      <td>177.528</td>\n",
       "      <td>25.294</td>\n",
       "      <td>71.677</td>\n",
       "      <td>236.044</td>\n",
       "      <td>3.803</td>\n",
       "      <td>39.368</td>\n",
       "      <td>358.052</td>\n",
       "      <td>104.312</td>\n",
       "      <td>166.530</td>\n",
       "      <td>51.570</td>\n",
       "      <td>50.337</td>\n",
       "      <td>280.993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>56.637</td>\n",
       "      <td>323.724</td>\n",
       "      <td>1138.865</td>\n",
       "      <td>930.634</td>\n",
       "      <td>107.632</td>\n",
       "      <td>1033.974</td>\n",
       "      <td>147.755</td>\n",
       "      <td>172.235</td>\n",
       "      <td>27.002</td>\n",
       "      <td>92.805</td>\n",
       "      <td>135.466</td>\n",
       "      <td>4.424</td>\n",
       "      <td>50.492</td>\n",
       "      <td>434.458</td>\n",
       "      <td>125.726</td>\n",
       "      <td>222.564</td>\n",
       "      <td>57.323</td>\n",
       "      <td>62.565</td>\n",
       "      <td>350.575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>81.051</td>\n",
       "      <td>369.367</td>\n",
       "      <td>1244.444</td>\n",
       "      <td>1145.360</td>\n",
       "      <td>135.846</td>\n",
       "      <td>1203.667</td>\n",
       "      <td>172.615</td>\n",
       "      <td>173.720</td>\n",
       "      <td>30.705</td>\n",
       "      <td>100.121</td>\n",
       "      <td>103.455</td>\n",
       "      <td>5.498</td>\n",
       "      <td>48.371</td>\n",
       "      <td>556.349</td>\n",
       "      <td>143.334</td>\n",
       "      <td>264.467</td>\n",
       "      <td>66.970</td>\n",
       "      <td>74.153</td>\n",
       "      <td>430.363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>115.565</td>\n",
       "      <td>487.082</td>\n",
       "      <td>1150.584</td>\n",
       "      <td>1456.125</td>\n",
       "      <td>113.365</td>\n",
       "      <td>1453.527</td>\n",
       "      <td>210.000</td>\n",
       "      <td>185.883</td>\n",
       "      <td>38.349</td>\n",
       "      <td>107.237</td>\n",
       "      <td>110.000</td>\n",
       "      <td>7.523</td>\n",
       "      <td>51.196</td>\n",
       "      <td>738.537</td>\n",
       "      <td>169.396</td>\n",
       "      <td>339.161</td>\n",
       "      <td>82.301</td>\n",
       "      <td>94.246</td>\n",
       "      <td>537.715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>177.030</td>\n",
       "      <td>424.565</td>\n",
       "      <td>1165.707</td>\n",
       "      <td>1684.490</td>\n",
       "      <td>124.325</td>\n",
       "      <td>2249.917</td>\n",
       "      <td>323.537</td>\n",
       "      <td>216.694</td>\n",
       "      <td>51.439</td>\n",
       "      <td>116.470</td>\n",
       "      <td>146.240</td>\n",
       "      <td>10.779</td>\n",
       "      <td>59.555</td>\n",
       "      <td>1099.917</td>\n",
       "      <td>173.764</td>\n",
       "      <td>412.606</td>\n",
       "      <td>106.962</td>\n",
       "      <td>118.540</td>\n",
       "      <td>697.501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>239.289</td>\n",
       "      <td>379.480</td>\n",
       "      <td>946.495</td>\n",
       "      <td>1755.136</td>\n",
       "      <td>178.980</td>\n",
       "      <td>2417.118</td>\n",
       "      <td>350.509</td>\n",
       "      <td>208.712</td>\n",
       "      <td>59.141</td>\n",
       "      <td>101.338</td>\n",
       "      <td>147.930</td>\n",
       "      <td>13.245</td>\n",
       "      <td>70.872</td>\n",
       "      <td>1378.922</td>\n",
       "      <td>174.803</td>\n",
       "      <td>485.999</td>\n",
       "      <td>117.338</td>\n",
       "      <td>137.046</td>\n",
       "      <td>805.223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>283.076</td>\n",
       "      <td>462.233</td>\n",
       "      <td>921.634</td>\n",
       "      <td>1944.897</td>\n",
       "      <td>154.875</td>\n",
       "      <td>2515.772</td>\n",
       "      <td>367.709</td>\n",
       "      <td>214.333</td>\n",
       "      <td>66.868</td>\n",
       "      <td>70.791</td>\n",
       "      <td>118.986</td>\n",
       "      <td>15.432</td>\n",
       "      <td>80.861</td>\n",
       "      <td>1555.616</td>\n",
       "      <td>238.286</td>\n",
       "      <td>551.071</td>\n",
       "      <td>126.374</td>\n",
       "      <td>153.395</td>\n",
       "      <td>688.753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>349.472</td>\n",
       "      <td>518.317</td>\n",
       "      <td>1213.465</td>\n",
       "      <td>1766.135</td>\n",
       "      <td>152.176</td>\n",
       "      <td>2915.490</td>\n",
       "      <td>428.612</td>\n",
       "      <td>257.204</td>\n",
       "      <td>82.843</td>\n",
       "      <td>74.544</td>\n",
       "      <td>135.474</td>\n",
       "      <td>19.295</td>\n",
       "      <td>101.491</td>\n",
       "      <td>1818.272</td>\n",
       "      <td>279.558</td>\n",
       "      <td>652.845</td>\n",
       "      <td>157.687</td>\n",
       "      <td>185.463</td>\n",
       "      <td>809.119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>476.221</td>\n",
       "      <td>550.862</td>\n",
       "      <td>1699.609</td>\n",
       "      <td>1991.904</td>\n",
       "      <td>217.913</td>\n",
       "      <td>3135.417</td>\n",
       "      <td>469.472</td>\n",
       "      <td>300.753</td>\n",
       "      <td>107.056</td>\n",
       "      <td>53.042</td>\n",
       "      <td>163.347</td>\n",
       "      <td>25.602</td>\n",
       "      <td>112.720</td>\n",
       "      <td>2388.071</td>\n",
       "      <td>283.140</td>\n",
       "      <td>805.144</td>\n",
       "      <td>202.924</td>\n",
       "      <td>233.347</td>\n",
       "      <td>1096.507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>439.000</td>\n",
       "      <td>1473.000</td>\n",
       "      <td>6424.000</td>\n",
       "      <td>2779.000</td>\n",
       "      <td>566.000</td>\n",
       "      <td>5945.000</td>\n",
       "      <td>887.000</td>\n",
       "      <td>830.000</td>\n",
       "      <td>327.000</td>\n",
       "      <td>73.000</td>\n",
       "      <td>10744.000</td>\n",
       "      <td>315.000</td>\n",
       "      <td>265.000</td>\n",
       "      <td>4132.000</td>\n",
       "      <td>69.000</td>\n",
       "      <td>1689.000</td>\n",
       "      <td>346.000</td>\n",
       "      <td>482.000</td>\n",
       "      <td>2083.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>447.000</td>\n",
       "      <td>1798.000</td>\n",
       "      <td>8169.000</td>\n",
       "      <td>3603.000</td>\n",
       "      <td>524.000</td>\n",
       "      <td>6874.000</td>\n",
       "      <td>827.000</td>\n",
       "      <td>1030.000</td>\n",
       "      <td>419.000</td>\n",
       "      <td>71.000</td>\n",
       "      <td>12855.000</td>\n",
       "      <td>328.000</td>\n",
       "      <td>256.000</td>\n",
       "      <td>4520.000</td>\n",
       "      <td>85.000</td>\n",
       "      <td>1918.000</td>\n",
       "      <td>2146.000</td>\n",
       "      <td>509.000</td>\n",
       "      <td>2116.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>584.000</td>\n",
       "      <td>2431.000</td>\n",
       "      <td>10988.000</td>\n",
       "      <td>4444.000</td>\n",
       "      <td>568.000</td>\n",
       "      <td>7747.000</td>\n",
       "      <td>760.000</td>\n",
       "      <td>1334.000</td>\n",
       "      <td>591.000</td>\n",
       "      <td>77.000</td>\n",
       "      <td>14184.000</td>\n",
       "      <td>392.000</td>\n",
       "      <td>325.000</td>\n",
       "      <td>5308.000</td>\n",
       "      <td>111.000</td>\n",
       "      <td>1923.000</td>\n",
       "      <td>482.000</td>\n",
       "      <td>543.000</td>\n",
       "      <td>2188.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>740.000</td>\n",
       "      <td>2937.000</td>\n",
       "      <td>13182.000</td>\n",
       "      <td>4576.000</td>\n",
       "      <td>629.000</td>\n",
       "      <td>9254.000</td>\n",
       "      <td>784.000</td>\n",
       "      <td>1494.000</td>\n",
       "      <td>757.000</td>\n",
       "      <td>69.000</td>\n",
       "      <td>16694.000</td>\n",
       "      <td>494.000</td>\n",
       "      <td>316.000</td>\n",
       "      <td>5811.000</td>\n",
       "      <td>140.000</td>\n",
       "      <td>1884.000</td>\n",
       "      <td>544.000</td>\n",
       "      <td>669.000</td>\n",
       "      <td>2192.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>936.000</td>\n",
       "      <td>3681.000</td>\n",
       "      <td>17506.000</td>\n",
       "      <td>4817.000</td>\n",
       "      <td>748.000</td>\n",
       "      <td>9760.000</td>\n",
       "      <td>770.000</td>\n",
       "      <td>1853.000</td>\n",
       "      <td>1033.000</td>\n",
       "      <td>81.000</td>\n",
       "      <td>21125.000</td>\n",
       "      <td>630.000</td>\n",
       "      <td>343.000</td>\n",
       "      <td>6989.000</td>\n",
       "      <td>178.000</td>\n",
       "      <td>1880.000</td>\n",
       "      <td>589.000</td>\n",
       "      <td>886.000</td>\n",
       "      <td>2194.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>1406.000</td>\n",
       "      <td>4326.000</td>\n",
       "      <td>21874.000</td>\n",
       "      <td>5286.000</td>\n",
       "      <td>815.000</td>\n",
       "      <td>10783.000</td>\n",
       "      <td>927.000</td>\n",
       "      <td>2289.000</td>\n",
       "      <td>1288.000</td>\n",
       "      <td>116.000</td>\n",
       "      <td>25978.000</td>\n",
       "      <td>893.000</td>\n",
       "      <td>461.000</td>\n",
       "      <td>8975.000</td>\n",
       "      <td>211.000</td>\n",
       "      <td>1898.000</td>\n",
       "      <td>731.000</td>\n",
       "      <td>1069.000</td>\n",
       "      <td>2420.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>1990.000</td>\n",
       "      <td>4608.000</td>\n",
       "      <td>26047.000</td>\n",
       "      <td>6363.000</td>\n",
       "      <td>1054.000</td>\n",
       "      <td>15375.000</td>\n",
       "      <td>1094.000</td>\n",
       "      <td>3005.000</td>\n",
       "      <td>1605.000</td>\n",
       "      <td>175.000</td>\n",
       "      <td>29877.000</td>\n",
       "      <td>1239.000</td>\n",
       "      <td>644.000</td>\n",
       "      <td>12277.000</td>\n",
       "      <td>319.000</td>\n",
       "      <td>2464.000</td>\n",
       "      <td>1166.000</td>\n",
       "      <td>1465.000</td>\n",
       "      <td>2932.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>2239.000</td>\n",
       "      <td>5163.000</td>\n",
       "      <td>32161.000</td>\n",
       "      <td>6473.000</td>\n",
       "      <td>1479.000</td>\n",
       "      <td>17868.000</td>\n",
       "      <td>922.000</td>\n",
       "      <td>3212.000</td>\n",
       "      <td>1957.000</td>\n",
       "      <td>237.000</td>\n",
       "      <td>36918.000</td>\n",
       "      <td>1536.000</td>\n",
       "      <td>680.000</td>\n",
       "      <td>14998.000</td>\n",
       "      <td>451.000</td>\n",
       "      <td>2760.000</td>\n",
       "      <td>1281.000</td>\n",
       "      <td>1729.000</td>\n",
       "      <td>3295.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>3833.000</td>\n",
       "      <td>5937.000</td>\n",
       "      <td>42876.000</td>\n",
       "      <td>6415.000</td>\n",
       "      <td>2091.000</td>\n",
       "      <td>16786.000</td>\n",
       "      <td>934.000</td>\n",
       "      <td>4337.000</td>\n",
       "      <td>2512.000</td>\n",
       "      <td>340.000</td>\n",
       "      <td>46889.000</td>\n",
       "      <td>1977.000</td>\n",
       "      <td>927.000</td>\n",
       "      <td>15981.000</td>\n",
       "      <td>689.000</td>\n",
       "      <td>2629.000</td>\n",
       "      <td>1465.000</td>\n",
       "      <td>1928.000</td>\n",
       "      <td>3834.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>4678.000</td>\n",
       "      <td>6290.000</td>\n",
       "      <td>49054.000</td>\n",
       "      <td>6789.000</td>\n",
       "      <td>2268.000</td>\n",
       "      <td>16586.000</td>\n",
       "      <td>1107.000</td>\n",
       "      <td>5334.000</td>\n",
       "      <td>2944.000</td>\n",
       "      <td>422.000</td>\n",
       "      <td>53366.000</td>\n",
       "      <td>2611.000</td>\n",
       "      <td>1218.000</td>\n",
       "      <td>17681.000</td>\n",
       "      <td>922.000</td>\n",
       "      <td>2888.000</td>\n",
       "      <td>1467.000</td>\n",
       "      <td>2444.000</td>\n",
       "      <td>3769.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>5673.000</td>\n",
       "      <td>6679.000</td>\n",
       "      <td>53917.000</td>\n",
       "      <td>7561.000</td>\n",
       "      <td>1905.000</td>\n",
       "      <td>18008.000</td>\n",
       "      <td>1168.000</td>\n",
       "      <td>6453.000</td>\n",
       "      <td>3280.000</td>\n",
       "      <td>616.000</td>\n",
       "      <td>60107.000</td>\n",
       "      <td>3052.000</td>\n",
       "      <td>1425.000</td>\n",
       "      <td>21553.000</td>\n",
       "      <td>1049.000</td>\n",
       "      <td>3139.000</td>\n",
       "      <td>1644.000</td>\n",
       "      <td>2790.000</td>\n",
       "      <td>3454.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>6831.000</td>\n",
       "      <td>6280.000</td>\n",
       "      <td>58507.000</td>\n",
       "      <td>8247.000</td>\n",
       "      <td>2050.000</td>\n",
       "      <td>20219.000</td>\n",
       "      <td>1434.000</td>\n",
       "      <td>7499.000</td>\n",
       "      <td>3202.000</td>\n",
       "      <td>646.000</td>\n",
       "      <td>61448.000</td>\n",
       "      <td>3704.000</td>\n",
       "      <td>1808.000</td>\n",
       "      <td>24893.000</td>\n",
       "      <td>1140.000</td>\n",
       "      <td>3567.000</td>\n",
       "      <td>1884.000</td>\n",
       "      <td>3074.000</td>\n",
       "      <td>3858.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>8407.000</td>\n",
       "      <td>5285.000</td>\n",
       "      <td>59197.000</td>\n",
       "      <td>9209.000</td>\n",
       "      <td>2288.000</td>\n",
       "      <td>21697.000</td>\n",
       "      <td>1866.000</td>\n",
       "      <td>8244.000</td>\n",
       "      <td>3113.000</td>\n",
       "      <td>590.000</td>\n",
       "      <td>58507.000</td>\n",
       "      <td>4212.000</td>\n",
       "      <td>1932.000</td>\n",
       "      <td>27912.000</td>\n",
       "      <td>1208.000</td>\n",
       "      <td>3822.000</td>\n",
       "      <td>2331.000</td>\n",
       "      <td>3156.000</td>\n",
       "      <td>3928.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>10090.000</td>\n",
       "      <td>4138.000</td>\n",
       "      <td>62755.000</td>\n",
       "      <td>10401.000</td>\n",
       "      <td>2216.000</td>\n",
       "      <td>23911.000</td>\n",
       "      <td>2112.000</td>\n",
       "      <td>7871.000</td>\n",
       "      <td>2863.000</td>\n",
       "      <td>566.000</td>\n",
       "      <td>61634.000</td>\n",
       "      <td>5299.000</td>\n",
       "      <td>2293.000</td>\n",
       "      <td>33872.000</td>\n",
       "      <td>1221.000</td>\n",
       "      <td>4594.000</td>\n",
       "      <td>2879.000</td>\n",
       "      <td>3565.000</td>\n",
       "      <td>4046.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>11980.000</td>\n",
       "      <td>4020.000</td>\n",
       "      <td>69295.000</td>\n",
       "      <td>11541.000</td>\n",
       "      <td>1838.000</td>\n",
       "      <td>29471.000</td>\n",
       "      <td>2430.000</td>\n",
       "      <td>7930.000</td>\n",
       "      <td>3195.000</td>\n",
       "      <td>530.000</td>\n",
       "      <td>65329.000</td>\n",
       "      <td>6104.000</td>\n",
       "      <td>2643.000</td>\n",
       "      <td>43002.000</td>\n",
       "      <td>1311.000</td>\n",
       "      <td>5891.000</td>\n",
       "      <td>3657.000</td>\n",
       "      <td>4436.000</td>\n",
       "      <td>4340.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>14745.000</td>\n",
       "      <td>4586.000</td>\n",
       "      <td>84159.000</td>\n",
       "      <td>12190.000</td>\n",
       "      <td>1716.000</td>\n",
       "      <td>33652.000</td>\n",
       "      <td>2624.000</td>\n",
       "      <td>6940.000</td>\n",
       "      <td>3285.000</td>\n",
       "      <td>437.000</td>\n",
       "      <td>69000.000</td>\n",
       "      <td>7725.000</td>\n",
       "      <td>3267.000</td>\n",
       "      <td>49148.000</td>\n",
       "      <td>1281.000</td>\n",
       "      <td>7027.000</td>\n",
       "      <td>4291.000</td>\n",
       "      <td>5922.000</td>\n",
       "      <td>4094.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>15561.000</td>\n",
       "      <td>5962.000</td>\n",
       "      <td>89772.000</td>\n",
       "      <td>13318.000</td>\n",
       "      <td>248.000</td>\n",
       "      <td>36800.000</td>\n",
       "      <td>2978.000</td>\n",
       "      <td>5876.000</td>\n",
       "      <td>3385.000</td>\n",
       "      <td>451.000</td>\n",
       "      <td>76381.000</td>\n",
       "      <td>9293.000</td>\n",
       "      <td>3917.000</td>\n",
       "      <td>53594.000</td>\n",
       "      <td>1186.000</td>\n",
       "      <td>8563.000</td>\n",
       "      <td>4648.000</td>\n",
       "      <td>6941.000</td>\n",
       "      <td>3518.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>19243.000</td>\n",
       "      <td>5250.000</td>\n",
       "      <td>91119.000</td>\n",
       "      <td>15588.000</td>\n",
       "      <td>293.000</td>\n",
       "      <td>37869.000</td>\n",
       "      <td>3447.000</td>\n",
       "      <td>4638.000</td>\n",
       "      <td>3283.000</td>\n",
       "      <td>369.000</td>\n",
       "      <td>80132.000</td>\n",
       "      <td>9983.000</td>\n",
       "      <td>4058.000</td>\n",
       "      <td>54129.000</td>\n",
       "      <td>1189.000</td>\n",
       "      <td>9739.000</td>\n",
       "      <td>5795.000</td>\n",
       "      <td>7156.000</td>\n",
       "      <td>3285.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>23488.000</td>\n",
       "      <td>5989.000</td>\n",
       "      <td>115279.000</td>\n",
       "      <td>16717.000</td>\n",
       "      <td>318.000</td>\n",
       "      <td>40101.000</td>\n",
       "      <td>4257.000</td>\n",
       "      <td>4815.000</td>\n",
       "      <td>3708.000</td>\n",
       "      <td>381.000</td>\n",
       "      <td>89256.000</td>\n",
       "      <td>12071.000</td>\n",
       "      <td>4941.000</td>\n",
       "      <td>56310.000</td>\n",
       "      <td>1158.000</td>\n",
       "      <td>11272.000</td>\n",
       "      <td>7355.000</td>\n",
       "      <td>7830.000</td>\n",
       "      <td>2127.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>24745.000</td>\n",
       "      <td>6819.000</td>\n",
       "      <td>132801.000</td>\n",
       "      <td>18919.000</td>\n",
       "      <td>267.000</td>\n",
       "      <td>40737.000</td>\n",
       "      <td>4604.000</td>\n",
       "      <td>4980.000</td>\n",
       "      <td>3950.000</td>\n",
       "      <td>389.000</td>\n",
       "      <td>78431.000</td>\n",
       "      <td>13743.000</td>\n",
       "      <td>5964.000</td>\n",
       "      <td>59541.000</td>\n",
       "      <td>1381.000</td>\n",
       "      <td>11342.000</td>\n",
       "      <td>9340.000</td>\n",
       "      <td>8068.000</td>\n",
       "      <td>3089.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>24251.000</td>\n",
       "      <td>7404.000</td>\n",
       "      <td>146435.000</td>\n",
       "      <td>22302.000</td>\n",
       "      <td>369.000</td>\n",
       "      <td>42341.000</td>\n",
       "      <td>5123.000</td>\n",
       "      <td>4905.000</td>\n",
       "      <td>4277.000</td>\n",
       "      <td>399.000</td>\n",
       "      <td>69884.000</td>\n",
       "      <td>15385.000</td>\n",
       "      <td>7060.000</td>\n",
       "      <td>58352.000</td>\n",
       "      <td>1561.000</td>\n",
       "      <td>11474.000</td>\n",
       "      <td>8553.000</td>\n",
       "      <td>8186.000</td>\n",
       "      <td>1842.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <td>27326.000</td>\n",
       "      <td>7494.000</td>\n",
       "      <td>157668.000</td>\n",
       "      <td>27256.000</td>\n",
       "      <td>294.000</td>\n",
       "      <td>42449.000</td>\n",
       "      <td>5146.000</td>\n",
       "      <td>5111.000</td>\n",
       "      <td>5466.000</td>\n",
       "      <td>359.000</td>\n",
       "      <td>60169.000</td>\n",
       "      <td>15557.000</td>\n",
       "      <td>7391.000</td>\n",
       "      <td>58276.000</td>\n",
       "      <td>1500.000</td>\n",
       "      <td>10851.000</td>\n",
       "      <td>7413.000</td>\n",
       "      <td>7939.000</td>\n",
       "      <td>1529.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           农林牧渔        采矿          制造       电热燃水        建筑       交通运输  \\\n",
       "1985     13.771    78.175     171.906     93.600    16.934    120.744   \n",
       "1986     14.003    90.114     195.522    124.206    15.135    117.599   \n",
       "1987     14.151   101.142     217.242    153.066    13.315    113.915   \n",
       "1988     14.444   112.914     240.615    182.694    11.689    111.539   \n",
       "1989     14.623   123.554     261.621    210.218    10.019    108.407   \n",
       "1990     18.528   142.699     266.396    255.169     7.259    129.596   \n",
       "1991     23.930   174.012     341.831    304.627     9.011    214.283   \n",
       "1992     32.153   224.076     442.882    410.714    17.181    297.826   \n",
       "1993     35.609   270.665     681.454    592.155    88.614    611.545   \n",
       "1994     42.360   294.402     907.591    858.687   103.233    902.296   \n",
       "1995     56.637   323.724    1138.865    930.634   107.632   1033.974   \n",
       "1996     81.051   369.367    1244.444   1145.360   135.846   1203.667   \n",
       "1997    115.565   487.082    1150.584   1456.125   113.365   1453.527   \n",
       "1998    177.030   424.565    1165.707   1684.490   124.325   2249.917   \n",
       "1999    239.289   379.480     946.495   1755.136   178.980   2417.118   \n",
       "2000    283.076   462.233     921.634   1944.897   154.875   2515.772   \n",
       "2001    349.472   518.317    1213.465   1766.135   152.176   2915.490   \n",
       "2002    476.221   550.862    1699.609   1991.904   217.913   3135.417   \n",
       "2003    439.000  1473.000    6424.000   2779.000   566.000   5945.000   \n",
       "2004    447.000  1798.000    8169.000   3603.000   524.000   6874.000   \n",
       "2005    584.000  2431.000   10988.000   4444.000   568.000   7747.000   \n",
       "2006    740.000  2937.000   13182.000   4576.000   629.000   9254.000   \n",
       "2007    936.000  3681.000   17506.000   4817.000   748.000   9760.000   \n",
       "2008   1406.000  4326.000   21874.000   5286.000   815.000  10783.000   \n",
       "2009   1990.000  4608.000   26047.000   6363.000  1054.000  15375.000   \n",
       "2010   2239.000  5163.000   32161.000   6473.000  1479.000  17868.000   \n",
       "2011   3833.000  5937.000   42876.000   6415.000  2091.000  16786.000   \n",
       "2012   4678.000  6290.000   49054.000   6789.000  2268.000  16586.000   \n",
       "2013   5673.000  6679.000   53917.000   7561.000  1905.000  18008.000   \n",
       "2014   6831.000  6280.000   58507.000   8247.000  2050.000  20219.000   \n",
       "2015   8407.000  5285.000   59197.000   9209.000  2288.000  21697.000   \n",
       "2016  10090.000  4138.000   62755.000  10401.000  2216.000  23911.000   \n",
       "2017  11980.000  4020.000   69295.000  11541.000  1838.000  29471.000   \n",
       "2018  14745.000  4586.000   84159.000  12190.000  1716.000  33652.000   \n",
       "2019  15561.000  5962.000   89772.000  13318.000   248.000  36800.000   \n",
       "2020  19243.000  5250.000   91119.000  15588.000   293.000  37869.000   \n",
       "2021  23488.000  5989.000  115279.000  16717.000   318.000  40101.000   \n",
       "2022  24745.000  6819.000  132801.000  18919.000   267.000  40737.000   \n",
       "2023  24251.000  7404.000  146435.000  22302.000   369.000  42341.000   \n",
       "2024  27326.000  7494.000  157668.000  27256.000   294.000  42449.000   \n",
       "\n",
       "          信息软件      批发零售      住宿餐饮       金融        房地产       租赁商务      科学研究  \\\n",
       "1985    17.265    28.650     3.776    5.488     47.970      0.523    16.026   \n",
       "1986    16.894    28.536     3.873    7.010     42.939      0.554    16.007   \n",
       "1987    16.443    28.270     3.945    8.441     37.847      0.581    15.901   \n",
       "1988    16.178    28.309     4.056    9.919     33.302      0.613    15.965   \n",
       "1989    15.801    28.140     4.135   11.285     28.630      0.640    15.911   \n",
       "1990    18.542    25.355     3.694   10.523     10.488      0.567    14.665   \n",
       "1991    30.451    42.604     5.759   13.446     19.947      0.820    16.542   \n",
       "1992    42.762    94.215    11.317   23.803     41.679      1.390    23.322   \n",
       "1993    87.779   146.398    19.860   51.364    108.553      2.838    37.481   \n",
       "1994   128.837   177.528    25.294   71.677    236.044      3.803    39.368   \n",
       "1995   147.755   172.235    27.002   92.805    135.466      4.424    50.492   \n",
       "1996   172.615   173.720    30.705  100.121    103.455      5.498    48.371   \n",
       "1997   210.000   185.883    38.349  107.237    110.000      7.523    51.196   \n",
       "1998   323.537   216.694    51.439  116.470    146.240     10.779    59.555   \n",
       "1999   350.509   208.712    59.141  101.338    147.930     13.245    70.872   \n",
       "2000   367.709   214.333    66.868   70.791    118.986     15.432    80.861   \n",
       "2001   428.612   257.204    82.843   74.544    135.474     19.295   101.491   \n",
       "2002   469.472   300.753   107.056   53.042    163.347     25.602   112.720   \n",
       "2003   887.000   830.000   327.000   73.000  10744.000    315.000   265.000   \n",
       "2004   827.000  1030.000   419.000   71.000  12855.000    328.000   256.000   \n",
       "2005   760.000  1334.000   591.000   77.000  14184.000    392.000   325.000   \n",
       "2006   784.000  1494.000   757.000   69.000  16694.000    494.000   316.000   \n",
       "2007   770.000  1853.000  1033.000   81.000  21125.000    630.000   343.000   \n",
       "2008   927.000  2289.000  1288.000  116.000  25978.000    893.000   461.000   \n",
       "2009  1094.000  3005.000  1605.000  175.000  29877.000   1239.000   644.000   \n",
       "2010   922.000  3212.000  1957.000  237.000  36918.000   1536.000   680.000   \n",
       "2011   934.000  4337.000  2512.000  340.000  46889.000   1977.000   927.000   \n",
       "2012  1107.000  5334.000  2944.000  422.000  53366.000   2611.000  1218.000   \n",
       "2013  1168.000  6453.000  3280.000  616.000  60107.000   3052.000  1425.000   \n",
       "2014  1434.000  7499.000  3202.000  646.000  61448.000   3704.000  1808.000   \n",
       "2015  1866.000  8244.000  3113.000  590.000  58507.000   4212.000  1932.000   \n",
       "2016  2112.000  7871.000  2863.000  566.000  61634.000   5299.000  2293.000   \n",
       "2017  2430.000  7930.000  3195.000  530.000  65329.000   6104.000  2643.000   \n",
       "2018  2624.000  6940.000  3285.000  437.000  69000.000   7725.000  3267.000   \n",
       "2019  2978.000  5876.000  3385.000  451.000  76381.000   9293.000  3917.000   \n",
       "2020  3447.000  4638.000  3283.000  369.000  80132.000   9983.000  4058.000   \n",
       "2021  4257.000  4815.000  3708.000  381.000  89256.000  12071.000  4941.000   \n",
       "2022  4604.000  4980.000  3950.000  389.000  78431.000  13743.000  5964.000   \n",
       "2023  5123.000  4905.000  4277.000  399.000  69884.000  15385.000  7060.000   \n",
       "2024  5146.000  5111.000  5466.000  359.000  60169.000  15557.000  7391.000   \n",
       "\n",
       "          水环公设施      居民服务         教育     卫生与社会       文体娱      公共管理  \n",
       "1985     56.281    39.316     51.314    13.121    13.946    38.202  \n",
       "1986     60.152    50.912     54.143    13.653    14.649    39.283  \n",
       "1987     63.558    61.825     56.576    14.091    15.247    40.109  \n",
       "1988     67.534    73.071     59.533    14.665    15.988    41.334  \n",
       "1989     70.912    83.490     61.978    15.117    16.592    42.225  \n",
       "1990     71.661    73.060     61.006    18.154    17.439    43.303  \n",
       "1991    100.010    43.564     72.865    17.326    19.409    62.758  \n",
       "1992    156.721   154.850     95.438    24.844    26.468   104.677  \n",
       "1993    275.841   102.410    134.415    37.652    39.012   232.236  \n",
       "1994    358.052   104.312    166.530    51.570    50.337   280.993  \n",
       "1995    434.458   125.726    222.564    57.323    62.565   350.575  \n",
       "1996    556.349   143.334    264.467    66.970    74.153   430.363  \n",
       "1997    738.537   169.396    339.161    82.301    94.246   537.715  \n",
       "1998   1099.917   173.764    412.606   106.962   118.540   697.501  \n",
       "1999   1378.922   174.803    485.999   117.338   137.046   805.223  \n",
       "2000   1555.616   238.286    551.071   126.374   153.395   688.753  \n",
       "2001   1818.272   279.558    652.845   157.687   185.463   809.119  \n",
       "2002   2388.071   283.140    805.144   202.924   233.347  1096.507  \n",
       "2003   4132.000    69.000   1689.000   346.000   482.000  2083.000  \n",
       "2004   4520.000    85.000   1918.000  2146.000   509.000  2116.000  \n",
       "2005   5308.000   111.000   1923.000   482.000   543.000  2188.000  \n",
       "2006   5811.000   140.000   1884.000   544.000   669.000  2192.000  \n",
       "2007   6989.000   178.000   1880.000   589.000   886.000  2194.000  \n",
       "2008   8975.000   211.000   1898.000   731.000  1069.000  2420.000  \n",
       "2009  12277.000   319.000   2464.000  1166.000  1465.000  2932.000  \n",
       "2010  14998.000   451.000   2760.000  1281.000  1729.000  3295.000  \n",
       "2011  15981.000   689.000   2629.000  1465.000  1928.000  3834.000  \n",
       "2012  17681.000   922.000   2888.000  1467.000  2444.000  3769.000  \n",
       "2013  21553.000  1049.000   3139.000  1644.000  2790.000  3454.000  \n",
       "2014  24893.000  1140.000   3567.000  1884.000  3074.000  3858.000  \n",
       "2015  27912.000  1208.000   3822.000  2331.000  3156.000  3928.000  \n",
       "2016  33872.000  1221.000   4594.000  2879.000  3565.000  4046.000  \n",
       "2017  43002.000  1311.000   5891.000  3657.000  4436.000  4340.000  \n",
       "2018  49148.000  1281.000   7027.000  4291.000  5922.000  4094.000  \n",
       "2019  53594.000  1186.000   8563.000  4648.000  6941.000  3518.000  \n",
       "2020  54129.000  1189.000   9739.000  5795.000  7156.000  3285.000  \n",
       "2021  56310.000  1158.000  11272.000  7355.000  7830.000  2127.000  \n",
       "2022  59541.000  1381.000  11342.000  9340.000  8068.000  3089.000  \n",
       "2023  58352.000  1561.000  11474.000  8553.000  8186.000  1842.000  \n",
       "2024  58276.000  1500.000  10851.000  7413.000  7939.000  1529.000  "
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_1985_2002 = pd.read_excel('data/kdata/计算得到1985-2002年19行业固定资产投资完成额.xlsx', index_col=0, sheet_name='建筑安装工程')\n",
    "build_ = pd.concat([build_1985_2002, build_2024], axis=0)\n",
    "build_.round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "d5015fe5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>4.119</td>\n",
       "      <td>23.385</td>\n",
       "      <td>51.424</td>\n",
       "      <td>28.000</td>\n",
       "      <td>5.066</td>\n",
       "      <td>36.120</td>\n",
       "      <td>5.165</td>\n",
       "      <td>8.570</td>\n",
       "      <td>1.130</td>\n",
       "      <td>1.642</td>\n",
       "      <td>14.350</td>\n",
       "      <td>0.156</td>\n",
       "      <td>4.794</td>\n",
       "      <td>16.836</td>\n",
       "      <td>11.761</td>\n",
       "      <td>15.350</td>\n",
       "      <td>3.925</td>\n",
       "      <td>4.172</td>\n",
       "      <td>11.428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986</th>\n",
       "      <td>4.464</td>\n",
       "      <td>28.726</td>\n",
       "      <td>62.328</td>\n",
       "      <td>39.594</td>\n",
       "      <td>4.825</td>\n",
       "      <td>37.488</td>\n",
       "      <td>5.385</td>\n",
       "      <td>9.097</td>\n",
       "      <td>1.235</td>\n",
       "      <td>2.235</td>\n",
       "      <td>13.688</td>\n",
       "      <td>0.177</td>\n",
       "      <td>5.103</td>\n",
       "      <td>19.175</td>\n",
       "      <td>16.230</td>\n",
       "      <td>17.260</td>\n",
       "      <td>4.352</td>\n",
       "      <td>4.670</td>\n",
       "      <td>12.522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987</th>\n",
       "      <td>4.894</td>\n",
       "      <td>34.978</td>\n",
       "      <td>75.128</td>\n",
       "      <td>52.934</td>\n",
       "      <td>4.605</td>\n",
       "      <td>39.395</td>\n",
       "      <td>5.686</td>\n",
       "      <td>9.777</td>\n",
       "      <td>1.364</td>\n",
       "      <td>2.919</td>\n",
       "      <td>13.088</td>\n",
       "      <td>0.201</td>\n",
       "      <td>5.499</td>\n",
       "      <td>21.980</td>\n",
       "      <td>21.381</td>\n",
       "      <td>19.565</td>\n",
       "      <td>4.873</td>\n",
       "      <td>5.273</td>\n",
       "      <td>13.871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988</th>\n",
       "      <td>5.179</td>\n",
       "      <td>40.486</td>\n",
       "      <td>86.275</td>\n",
       "      <td>65.506</td>\n",
       "      <td>4.191</td>\n",
       "      <td>39.993</td>\n",
       "      <td>5.801</td>\n",
       "      <td>10.151</td>\n",
       "      <td>1.454</td>\n",
       "      <td>3.556</td>\n",
       "      <td>11.941</td>\n",
       "      <td>0.220</td>\n",
       "      <td>5.725</td>\n",
       "      <td>24.215</td>\n",
       "      <td>26.200</td>\n",
       "      <td>21.346</td>\n",
       "      <td>5.258</td>\n",
       "      <td>5.733</td>\n",
       "      <td>14.821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989</th>\n",
       "      <td>5.577</td>\n",
       "      <td>47.126</td>\n",
       "      <td>99.789</td>\n",
       "      <td>80.182</td>\n",
       "      <td>3.821</td>\n",
       "      <td>41.349</td>\n",
       "      <td>6.027</td>\n",
       "      <td>10.733</td>\n",
       "      <td>1.577</td>\n",
       "      <td>4.305</td>\n",
       "      <td>10.920</td>\n",
       "      <td>0.244</td>\n",
       "      <td>6.069</td>\n",
       "      <td>27.047</td>\n",
       "      <td>31.845</td>\n",
       "      <td>23.640</td>\n",
       "      <td>5.766</td>\n",
       "      <td>6.329</td>\n",
       "      <td>16.105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990</th>\n",
       "      <td>8.042</td>\n",
       "      <td>61.941</td>\n",
       "      <td>115.634</td>\n",
       "      <td>110.761</td>\n",
       "      <td>3.151</td>\n",
       "      <td>56.253</td>\n",
       "      <td>8.048</td>\n",
       "      <td>11.006</td>\n",
       "      <td>1.603</td>\n",
       "      <td>4.567</td>\n",
       "      <td>4.552</td>\n",
       "      <td>0.246</td>\n",
       "      <td>6.365</td>\n",
       "      <td>31.106</td>\n",
       "      <td>31.713</td>\n",
       "      <td>26.481</td>\n",
       "      <td>7.880</td>\n",
       "      <td>7.570</td>\n",
       "      <td>18.797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991</th>\n",
       "      <td>9.530</td>\n",
       "      <td>69.298</td>\n",
       "      <td>136.129</td>\n",
       "      <td>121.313</td>\n",
       "      <td>3.589</td>\n",
       "      <td>85.335</td>\n",
       "      <td>12.126</td>\n",
       "      <td>16.966</td>\n",
       "      <td>2.294</td>\n",
       "      <td>5.354</td>\n",
       "      <td>7.943</td>\n",
       "      <td>0.327</td>\n",
       "      <td>6.588</td>\n",
       "      <td>39.827</td>\n",
       "      <td>17.349</td>\n",
       "      <td>29.017</td>\n",
       "      <td>6.900</td>\n",
       "      <td>7.729</td>\n",
       "      <td>24.992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992</th>\n",
       "      <td>11.357</td>\n",
       "      <td>79.144</td>\n",
       "      <td>156.428</td>\n",
       "      <td>145.066</td>\n",
       "      <td>6.069</td>\n",
       "      <td>105.193</td>\n",
       "      <td>15.104</td>\n",
       "      <td>33.277</td>\n",
       "      <td>3.997</td>\n",
       "      <td>8.407</td>\n",
       "      <td>14.721</td>\n",
       "      <td>0.491</td>\n",
       "      <td>8.238</td>\n",
       "      <td>55.354</td>\n",
       "      <td>54.694</td>\n",
       "      <td>33.709</td>\n",
       "      <td>8.775</td>\n",
       "      <td>9.349</td>\n",
       "      <td>36.973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993</th>\n",
       "      <td>10.611</td>\n",
       "      <td>80.655</td>\n",
       "      <td>203.066</td>\n",
       "      <td>176.455</td>\n",
       "      <td>26.406</td>\n",
       "      <td>182.233</td>\n",
       "      <td>26.157</td>\n",
       "      <td>43.625</td>\n",
       "      <td>5.918</td>\n",
       "      <td>15.306</td>\n",
       "      <td>32.347</td>\n",
       "      <td>0.846</td>\n",
       "      <td>11.169</td>\n",
       "      <td>82.197</td>\n",
       "      <td>30.517</td>\n",
       "      <td>40.054</td>\n",
       "      <td>11.220</td>\n",
       "      <td>11.625</td>\n",
       "      <td>69.204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994</th>\n",
       "      <td>14.410</td>\n",
       "      <td>100.148</td>\n",
       "      <td>308.739</td>\n",
       "      <td>292.103</td>\n",
       "      <td>35.117</td>\n",
       "      <td>306.937</td>\n",
       "      <td>43.827</td>\n",
       "      <td>60.391</td>\n",
       "      <td>8.605</td>\n",
       "      <td>24.383</td>\n",
       "      <td>80.296</td>\n",
       "      <td>1.294</td>\n",
       "      <td>13.392</td>\n",
       "      <td>121.800</td>\n",
       "      <td>35.484</td>\n",
       "      <td>56.649</td>\n",
       "      <td>17.543</td>\n",
       "      <td>17.123</td>\n",
       "      <td>95.587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995</th>\n",
       "      <td>19.953</td>\n",
       "      <td>114.046</td>\n",
       "      <td>401.215</td>\n",
       "      <td>327.856</td>\n",
       "      <td>37.918</td>\n",
       "      <td>364.262</td>\n",
       "      <td>52.053</td>\n",
       "      <td>60.677</td>\n",
       "      <td>9.513</td>\n",
       "      <td>32.695</td>\n",
       "      <td>47.724</td>\n",
       "      <td>1.559</td>\n",
       "      <td>17.788</td>\n",
       "      <td>153.057</td>\n",
       "      <td>44.292</td>\n",
       "      <td>78.408</td>\n",
       "      <td>20.195</td>\n",
       "      <td>22.041</td>\n",
       "      <td>123.505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>28.349</td>\n",
       "      <td>129.193</td>\n",
       "      <td>435.266</td>\n",
       "      <td>400.610</td>\n",
       "      <td>47.514</td>\n",
       "      <td>421.004</td>\n",
       "      <td>60.375</td>\n",
       "      <td>60.762</td>\n",
       "      <td>10.740</td>\n",
       "      <td>35.019</td>\n",
       "      <td>36.185</td>\n",
       "      <td>1.923</td>\n",
       "      <td>16.919</td>\n",
       "      <td>194.593</td>\n",
       "      <td>50.134</td>\n",
       "      <td>92.502</td>\n",
       "      <td>23.424</td>\n",
       "      <td>25.936</td>\n",
       "      <td>150.527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>38.315</td>\n",
       "      <td>161.488</td>\n",
       "      <td>381.466</td>\n",
       "      <td>482.765</td>\n",
       "      <td>37.585</td>\n",
       "      <td>481.904</td>\n",
       "      <td>69.623</td>\n",
       "      <td>61.628</td>\n",
       "      <td>12.714</td>\n",
       "      <td>35.553</td>\n",
       "      <td>36.470</td>\n",
       "      <td>2.494</td>\n",
       "      <td>16.974</td>\n",
       "      <td>244.855</td>\n",
       "      <td>56.162</td>\n",
       "      <td>112.446</td>\n",
       "      <td>27.286</td>\n",
       "      <td>31.246</td>\n",
       "      <td>178.275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>48.350</td>\n",
       "      <td>115.955</td>\n",
       "      <td>318.373</td>\n",
       "      <td>460.060</td>\n",
       "      <td>33.955</td>\n",
       "      <td>614.488</td>\n",
       "      <td>88.363</td>\n",
       "      <td>59.183</td>\n",
       "      <td>14.049</td>\n",
       "      <td>31.810</td>\n",
       "      <td>39.940</td>\n",
       "      <td>2.944</td>\n",
       "      <td>16.265</td>\n",
       "      <td>300.405</td>\n",
       "      <td>47.458</td>\n",
       "      <td>112.689</td>\n",
       "      <td>29.213</td>\n",
       "      <td>32.375</td>\n",
       "      <td>190.499</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>59.721</td>\n",
       "      <td>94.710</td>\n",
       "      <td>236.225</td>\n",
       "      <td>438.044</td>\n",
       "      <td>44.670</td>\n",
       "      <td>603.261</td>\n",
       "      <td>87.479</td>\n",
       "      <td>52.090</td>\n",
       "      <td>14.760</td>\n",
       "      <td>25.292</td>\n",
       "      <td>36.920</td>\n",
       "      <td>3.306</td>\n",
       "      <td>17.688</td>\n",
       "      <td>344.149</td>\n",
       "      <td>43.627</td>\n",
       "      <td>121.295</td>\n",
       "      <td>29.285</td>\n",
       "      <td>34.204</td>\n",
       "      <td>200.967</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>77.854</td>\n",
       "      <td>127.127</td>\n",
       "      <td>253.476</td>\n",
       "      <td>534.903</td>\n",
       "      <td>42.595</td>\n",
       "      <td>691.910</td>\n",
       "      <td>101.131</td>\n",
       "      <td>58.948</td>\n",
       "      <td>18.391</td>\n",
       "      <td>19.469</td>\n",
       "      <td>32.724</td>\n",
       "      <td>4.244</td>\n",
       "      <td>22.239</td>\n",
       "      <td>427.839</td>\n",
       "      <td>65.536</td>\n",
       "      <td>151.560</td>\n",
       "      <td>34.757</td>\n",
       "      <td>42.188</td>\n",
       "      <td>189.427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>85.118</td>\n",
       "      <td>126.243</td>\n",
       "      <td>295.555</td>\n",
       "      <td>430.165</td>\n",
       "      <td>37.064</td>\n",
       "      <td>710.105</td>\n",
       "      <td>104.394</td>\n",
       "      <td>62.645</td>\n",
       "      <td>20.177</td>\n",
       "      <td>18.156</td>\n",
       "      <td>32.996</td>\n",
       "      <td>4.700</td>\n",
       "      <td>24.719</td>\n",
       "      <td>442.863</td>\n",
       "      <td>68.090</td>\n",
       "      <td>159.009</td>\n",
       "      <td>38.407</td>\n",
       "      <td>45.172</td>\n",
       "      <td>197.071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>111.579</td>\n",
       "      <td>129.068</td>\n",
       "      <td>398.221</td>\n",
       "      <td>466.706</td>\n",
       "      <td>51.057</td>\n",
       "      <td>734.633</td>\n",
       "      <td>109.998</td>\n",
       "      <td>70.467</td>\n",
       "      <td>25.084</td>\n",
       "      <td>12.428</td>\n",
       "      <td>38.273</td>\n",
       "      <td>5.998</td>\n",
       "      <td>26.410</td>\n",
       "      <td>559.529</td>\n",
       "      <td>66.340</td>\n",
       "      <td>188.646</td>\n",
       "      <td>47.546</td>\n",
       "      <td>54.673</td>\n",
       "      <td>256.913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>77.000</td>\n",
       "      <td>473.000</td>\n",
       "      <td>7278.000</td>\n",
       "      <td>1736.000</td>\n",
       "      <td>74.000</td>\n",
       "      <td>1031.000</td>\n",
       "      <td>1357.000</td>\n",
       "      <td>105.000</td>\n",
       "      <td>50.000</td>\n",
       "      <td>38.000</td>\n",
       "      <td>219.000</td>\n",
       "      <td>31.000</td>\n",
       "      <td>62.000</td>\n",
       "      <td>150.000</td>\n",
       "      <td>7.000</td>\n",
       "      <td>113.000</td>\n",
       "      <td>124.000</td>\n",
       "      <td>77.000</td>\n",
       "      <td>192.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>110.000</td>\n",
       "      <td>666.000</td>\n",
       "      <td>8835.000</td>\n",
       "      <td>2443.000</td>\n",
       "      <td>84.000</td>\n",
       "      <td>1124.000</td>\n",
       "      <td>1191.000</td>\n",
       "      <td>160.000</td>\n",
       "      <td>69.000</td>\n",
       "      <td>42.000</td>\n",
       "      <td>267.000</td>\n",
       "      <td>46.000</td>\n",
       "      <td>80.000</td>\n",
       "      <td>158.000</td>\n",
       "      <td>36.000</td>\n",
       "      <td>133.000</td>\n",
       "      <td>303.000</td>\n",
       "      <td>85.000</td>\n",
       "      <td>281.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>115.000</td>\n",
       "      <td>1015.000</td>\n",
       "      <td>11107.000</td>\n",
       "      <td>3052.000</td>\n",
       "      <td>115.000</td>\n",
       "      <td>1386.000</td>\n",
       "      <td>999.000</td>\n",
       "      <td>223.000</td>\n",
       "      <td>91.000</td>\n",
       "      <td>35.000</td>\n",
       "      <td>307.000</td>\n",
       "      <td>53.000</td>\n",
       "      <td>90.000</td>\n",
       "      <td>184.000</td>\n",
       "      <td>24.000</td>\n",
       "      <td>165.000</td>\n",
       "      <td>160.000</td>\n",
       "      <td>94.000</td>\n",
       "      <td>361.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>156.000</td>\n",
       "      <td>1134.000</td>\n",
       "      <td>13217.000</td>\n",
       "      <td>3253.000</td>\n",
       "      <td>165.000</td>\n",
       "      <td>1439.000</td>\n",
       "      <td>1080.000</td>\n",
       "      <td>259.000</td>\n",
       "      <td>128.000</td>\n",
       "      <td>48.000</td>\n",
       "      <td>349.000</td>\n",
       "      <td>60.000</td>\n",
       "      <td>116.000</td>\n",
       "      <td>255.000</td>\n",
       "      <td>37.000</td>\n",
       "      <td>183.000</td>\n",
       "      <td>163.000</td>\n",
       "      <td>113.000</td>\n",
       "      <td>402.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>212.000</td>\n",
       "      <td>1372.000</td>\n",
       "      <td>16498.000</td>\n",
       "      <td>3422.000</td>\n",
       "      <td>193.000</td>\n",
       "      <td>2071.000</td>\n",
       "      <td>1066.000</td>\n",
       "      <td>329.000</td>\n",
       "      <td>168.000</td>\n",
       "      <td>64.000</td>\n",
       "      <td>430.000</td>\n",
       "      <td>85.000</td>\n",
       "      <td>129.000</td>\n",
       "      <td>294.000</td>\n",
       "      <td>43.000</td>\n",
       "      <td>193.000</td>\n",
       "      <td>194.000</td>\n",
       "      <td>126.000</td>\n",
       "      <td>382.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>323.000</td>\n",
       "      <td>1917.000</td>\n",
       "      <td>20940.000</td>\n",
       "      <td>3902.000</td>\n",
       "      <td>261.000</td>\n",
       "      <td>2338.000</td>\n",
       "      <td>1122.000</td>\n",
       "      <td>495.000</td>\n",
       "      <td>236.000</td>\n",
       "      <td>102.000</td>\n",
       "      <td>554.000</td>\n",
       "      <td>139.000</td>\n",
       "      <td>169.000</td>\n",
       "      <td>414.000</td>\n",
       "      <td>67.000</td>\n",
       "      <td>234.000</td>\n",
       "      <td>242.000</td>\n",
       "      <td>165.000</td>\n",
       "      <td>461.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>423.000</td>\n",
       "      <td>2303.000</td>\n",
       "      <td>24489.000</td>\n",
       "      <td>4728.000</td>\n",
       "      <td>295.000</td>\n",
       "      <td>2631.000</td>\n",
       "      <td>1213.000</td>\n",
       "      <td>728.000</td>\n",
       "      <td>314.000</td>\n",
       "      <td>108.000</td>\n",
       "      <td>579.000</td>\n",
       "      <td>227.000</td>\n",
       "      <td>235.000</td>\n",
       "      <td>590.000</td>\n",
       "      <td>96.000</td>\n",
       "      <td>262.000</td>\n",
       "      <td>295.000</td>\n",
       "      <td>230.000</td>\n",
       "      <td>432.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>492.000</td>\n",
       "      <td>2629.000</td>\n",
       "      <td>29009.000</td>\n",
       "      <td>5183.000</td>\n",
       "      <td>355.000</td>\n",
       "      <td>3553.000</td>\n",
       "      <td>1103.000</td>\n",
       "      <td>828.000</td>\n",
       "      <td>339.000</td>\n",
       "      <td>121.000</td>\n",
       "      <td>713.000</td>\n",
       "      <td>303.000</td>\n",
       "      <td>276.000</td>\n",
       "      <td>763.000</td>\n",
       "      <td>93.000</td>\n",
       "      <td>274.000</td>\n",
       "      <td>335.000</td>\n",
       "      <td>272.000</td>\n",
       "      <td>437.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>881.000</td>\n",
       "      <td>2811.000</td>\n",
       "      <td>35530.000</td>\n",
       "      <td>4473.000</td>\n",
       "      <td>365.000</td>\n",
       "      <td>3227.000</td>\n",
       "      <td>773.000</td>\n",
       "      <td>950.000</td>\n",
       "      <td>362.000</td>\n",
       "      <td>123.000</td>\n",
       "      <td>980.000</td>\n",
       "      <td>369.000</td>\n",
       "      <td>263.000</td>\n",
       "      <td>839.000</td>\n",
       "      <td>134.000</td>\n",
       "      <td>243.000</td>\n",
       "      <td>310.000</td>\n",
       "      <td>285.000</td>\n",
       "      <td>391.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>1040.000</td>\n",
       "      <td>2841.000</td>\n",
       "      <td>38659.000</td>\n",
       "      <td>4648.000</td>\n",
       "      <td>356.000</td>\n",
       "      <td>3496.000</td>\n",
       "      <td>807.000</td>\n",
       "      <td>1153.000</td>\n",
       "      <td>459.000</td>\n",
       "      <td>138.000</td>\n",
       "      <td>1266.000</td>\n",
       "      <td>388.000</td>\n",
       "      <td>414.000</td>\n",
       "      <td>1069.000</td>\n",
       "      <td>198.000</td>\n",
       "      <td>303.000</td>\n",
       "      <td>360.000</td>\n",
       "      <td>353.000</td>\n",
       "      <td>408.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>1233.000</td>\n",
       "      <td>2683.000</td>\n",
       "      <td>41845.000</td>\n",
       "      <td>4797.000</td>\n",
       "      <td>402.000</td>\n",
       "      <td>3591.000</td>\n",
       "      <td>847.000</td>\n",
       "      <td>1350.000</td>\n",
       "      <td>459.000</td>\n",
       "      <td>148.000</td>\n",
       "      <td>1372.000</td>\n",
       "      <td>474.000</td>\n",
       "      <td>520.000</td>\n",
       "      <td>1292.000</td>\n",
       "      <td>201.000</td>\n",
       "      <td>286.000</td>\n",
       "      <td>393.000</td>\n",
       "      <td>374.000</td>\n",
       "      <td>306.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>1339.000</td>\n",
       "      <td>2293.000</td>\n",
       "      <td>41806.000</td>\n",
       "      <td>5174.000</td>\n",
       "      <td>393.000</td>\n",
       "      <td>3830.000</td>\n",
       "      <td>1083.000</td>\n",
       "      <td>1576.000</td>\n",
       "      <td>415.000</td>\n",
       "      <td>155.000</td>\n",
       "      <td>1360.000</td>\n",
       "      <td>823.000</td>\n",
       "      <td>663.000</td>\n",
       "      <td>1411.000</td>\n",
       "      <td>198.000</td>\n",
       "      <td>362.000</td>\n",
       "      <td>495.000</td>\n",
       "      <td>426.000</td>\n",
       "      <td>368.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>1578.000</td>\n",
       "      <td>1829.000</td>\n",
       "      <td>42080.000</td>\n",
       "      <td>5400.000</td>\n",
       "      <td>464.000</td>\n",
       "      <td>3842.000</td>\n",
       "      <td>1249.000</td>\n",
       "      <td>1993.000</td>\n",
       "      <td>421.000</td>\n",
       "      <td>129.000</td>\n",
       "      <td>1216.000</td>\n",
       "      <td>910.000</td>\n",
       "      <td>678.000</td>\n",
       "      <td>1610.000</td>\n",
       "      <td>243.000</td>\n",
       "      <td>450.000</td>\n",
       "      <td>516.000</td>\n",
       "      <td>446.000</td>\n",
       "      <td>382.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>1769.000</td>\n",
       "      <td>1416.000</td>\n",
       "      <td>42039.000</td>\n",
       "      <td>5741.000</td>\n",
       "      <td>365.000</td>\n",
       "      <td>3512.000</td>\n",
       "      <td>1399.000</td>\n",
       "      <td>1981.000</td>\n",
       "      <td>370.000</td>\n",
       "      <td>146.000</td>\n",
       "      <td>1415.000</td>\n",
       "      <td>1332.000</td>\n",
       "      <td>714.000</td>\n",
       "      <td>2001.000</td>\n",
       "      <td>246.000</td>\n",
       "      <td>442.000</td>\n",
       "      <td>571.000</td>\n",
       "      <td>489.000</td>\n",
       "      <td>408.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>1941.000</td>\n",
       "      <td>1270.000</td>\n",
       "      <td>46234.000</td>\n",
       "      <td>5788.000</td>\n",
       "      <td>322.000</td>\n",
       "      <td>3909.000</td>\n",
       "      <td>1674.000</td>\n",
       "      <td>1834.000</td>\n",
       "      <td>388.000</td>\n",
       "      <td>99.000</td>\n",
       "      <td>1526.000</td>\n",
       "      <td>1385.000</td>\n",
       "      <td>846.000</td>\n",
       "      <td>2458.000</td>\n",
       "      <td>263.000</td>\n",
       "      <td>517.000</td>\n",
       "      <td>654.000</td>\n",
       "      <td>500.000</td>\n",
       "      <td>403.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>2376.000</td>\n",
       "      <td>1435.000</td>\n",
       "      <td>53444.000</td>\n",
       "      <td>5417.000</td>\n",
       "      <td>322.000</td>\n",
       "      <td>4638.000</td>\n",
       "      <td>2025.000</td>\n",
       "      <td>1394.000</td>\n",
       "      <td>389.000</td>\n",
       "      <td>183.000</td>\n",
       "      <td>1637.000</td>\n",
       "      <td>1275.000</td>\n",
       "      <td>922.000</td>\n",
       "      <td>2684.000</td>\n",
       "      <td>215.000</td>\n",
       "      <td>550.000</td>\n",
       "      <td>768.000</td>\n",
       "      <td>621.000</td>\n",
       "      <td>282.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>2270.000</td>\n",
       "      <td>1727.000</td>\n",
       "      <td>55739.000</td>\n",
       "      <td>5403.000</td>\n",
       "      <td>109.000</td>\n",
       "      <td>3941.000</td>\n",
       "      <td>2202.000</td>\n",
       "      <td>1255.000</td>\n",
       "      <td>371.000</td>\n",
       "      <td>188.000</td>\n",
       "      <td>1795.000</td>\n",
       "      <td>1431.000</td>\n",
       "      <td>994.000</td>\n",
       "      <td>2622.000</td>\n",
       "      <td>210.000</td>\n",
       "      <td>564.000</td>\n",
       "      <td>865.000</td>\n",
       "      <td>619.000</td>\n",
       "      <td>270.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>2329.000</td>\n",
       "      <td>1439.000</td>\n",
       "      <td>51432.000</td>\n",
       "      <td>6682.000</td>\n",
       "      <td>78.000</td>\n",
       "      <td>2929.000</td>\n",
       "      <td>2563.000</td>\n",
       "      <td>677.000</td>\n",
       "      <td>213.000</td>\n",
       "      <td>101.000</td>\n",
       "      <td>1439.000</td>\n",
       "      <td>1181.000</td>\n",
       "      <td>962.000</td>\n",
       "      <td>1969.000</td>\n",
       "      <td>125.000</td>\n",
       "      <td>473.000</td>\n",
       "      <td>1155.000</td>\n",
       "      <td>520.000</td>\n",
       "      <td>236.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>1793.000</td>\n",
       "      <td>1494.000</td>\n",
       "      <td>54304.000</td>\n",
       "      <td>6557.000</td>\n",
       "      <td>93.000</td>\n",
       "      <td>3044.000</td>\n",
       "      <td>2966.000</td>\n",
       "      <td>414.000</td>\n",
       "      <td>157.000</td>\n",
       "      <td>156.000</td>\n",
       "      <td>1288.000</td>\n",
       "      <td>1121.000</td>\n",
       "      <td>1045.000</td>\n",
       "      <td>1114.000</td>\n",
       "      <td>96.000</td>\n",
       "      <td>572.000</td>\n",
       "      <td>1314.000</td>\n",
       "      <td>380.000</td>\n",
       "      <td>100.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>1532.000</td>\n",
       "      <td>1691.000</td>\n",
       "      <td>55217.000</td>\n",
       "      <td>8016.000</td>\n",
       "      <td>142.000</td>\n",
       "      <td>2778.000</td>\n",
       "      <td>2979.000</td>\n",
       "      <td>402.000</td>\n",
       "      <td>156.000</td>\n",
       "      <td>163.000</td>\n",
       "      <td>1105.000</td>\n",
       "      <td>842.000</td>\n",
       "      <td>1172.000</td>\n",
       "      <td>1069.000</td>\n",
       "      <td>89.000</td>\n",
       "      <td>548.000</td>\n",
       "      <td>1391.000</td>\n",
       "      <td>322.000</td>\n",
       "      <td>85.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>1420.000</td>\n",
       "      <td>1771.000</td>\n",
       "      <td>56244.000</td>\n",
       "      <td>10559.000</td>\n",
       "      <td>122.000</td>\n",
       "      <td>2250.000</td>\n",
       "      <td>3511.000</td>\n",
       "      <td>383.000</td>\n",
       "      <td>215.000</td>\n",
       "      <td>213.000</td>\n",
       "      <td>1020.000</td>\n",
       "      <td>960.000</td>\n",
       "      <td>1275.000</td>\n",
       "      <td>869.000</td>\n",
       "      <td>86.000</td>\n",
       "      <td>661.000</td>\n",
       "      <td>1586.000</td>\n",
       "      <td>243.000</td>\n",
       "      <td>80.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <td>1292.000</td>\n",
       "      <td>2009.000</td>\n",
       "      <td>57688.000</td>\n",
       "      <td>11847.000</td>\n",
       "      <td>195.000</td>\n",
       "      <td>3326.000</td>\n",
       "      <td>4058.000</td>\n",
       "      <td>446.000</td>\n",
       "      <td>246.000</td>\n",
       "      <td>187.000</td>\n",
       "      <td>741.000</td>\n",
       "      <td>1320.000</td>\n",
       "      <td>1661.000</td>\n",
       "      <td>1004.000</td>\n",
       "      <td>107.000</td>\n",
       "      <td>744.000</td>\n",
       "      <td>1353.000</td>\n",
       "      <td>251.000</td>\n",
       "      <td>187.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          农林牧渔        采矿         制造       电热燃水       建筑      交通运输      信息软件  \\\n",
       "1985     4.119    23.385     51.424     28.000    5.066    36.120     5.165   \n",
       "1986     4.464    28.726     62.328     39.594    4.825    37.488     5.385   \n",
       "1987     4.894    34.978     75.128     52.934    4.605    39.395     5.686   \n",
       "1988     5.179    40.486     86.275     65.506    4.191    39.993     5.801   \n",
       "1989     5.577    47.126     99.789     80.182    3.821    41.349     6.027   \n",
       "1990     8.042    61.941    115.634    110.761    3.151    56.253     8.048   \n",
       "1991     9.530    69.298    136.129    121.313    3.589    85.335    12.126   \n",
       "1992    11.357    79.144    156.428    145.066    6.069   105.193    15.104   \n",
       "1993    10.611    80.655    203.066    176.455   26.406   182.233    26.157   \n",
       "1994    14.410   100.148    308.739    292.103   35.117   306.937    43.827   \n",
       "1995    19.953   114.046    401.215    327.856   37.918   364.262    52.053   \n",
       "1996    28.349   129.193    435.266    400.610   47.514   421.004    60.375   \n",
       "1997    38.315   161.488    381.466    482.765   37.585   481.904    69.623   \n",
       "1998    48.350   115.955    318.373    460.060   33.955   614.488    88.363   \n",
       "1999    59.721    94.710    236.225    438.044   44.670   603.261    87.479   \n",
       "2000    77.854   127.127    253.476    534.903   42.595   691.910   101.131   \n",
       "2001    85.118   126.243    295.555    430.165   37.064   710.105   104.394   \n",
       "2002   111.579   129.068    398.221    466.706   51.057   734.633   109.998   \n",
       "2003    77.000   473.000   7278.000   1736.000   74.000  1031.000  1357.000   \n",
       "2004   110.000   666.000   8835.000   2443.000   84.000  1124.000  1191.000   \n",
       "2005   115.000  1015.000  11107.000   3052.000  115.000  1386.000   999.000   \n",
       "2006   156.000  1134.000  13217.000   3253.000  165.000  1439.000  1080.000   \n",
       "2007   212.000  1372.000  16498.000   3422.000  193.000  2071.000  1066.000   \n",
       "2008   323.000  1917.000  20940.000   3902.000  261.000  2338.000  1122.000   \n",
       "2009   423.000  2303.000  24489.000   4728.000  295.000  2631.000  1213.000   \n",
       "2010   492.000  2629.000  29009.000   5183.000  355.000  3553.000  1103.000   \n",
       "2011   881.000  2811.000  35530.000   4473.000  365.000  3227.000   773.000   \n",
       "2012  1040.000  2841.000  38659.000   4648.000  356.000  3496.000   807.000   \n",
       "2013  1233.000  2683.000  41845.000   4797.000  402.000  3591.000   847.000   \n",
       "2014  1339.000  2293.000  41806.000   5174.000  393.000  3830.000  1083.000   \n",
       "2015  1578.000  1829.000  42080.000   5400.000  464.000  3842.000  1249.000   \n",
       "2016  1769.000  1416.000  42039.000   5741.000  365.000  3512.000  1399.000   \n",
       "2017  1941.000  1270.000  46234.000   5788.000  322.000  3909.000  1674.000   \n",
       "2018  2376.000  1435.000  53444.000   5417.000  322.000  4638.000  2025.000   \n",
       "2019  2270.000  1727.000  55739.000   5403.000  109.000  3941.000  2202.000   \n",
       "2020  2329.000  1439.000  51432.000   6682.000   78.000  2929.000  2563.000   \n",
       "2021  1793.000  1494.000  54304.000   6557.000   93.000  3044.000  2966.000   \n",
       "2022  1532.000  1691.000  55217.000   8016.000  142.000  2778.000  2979.000   \n",
       "2023  1420.000  1771.000  56244.000  10559.000  122.000  2250.000  3511.000   \n",
       "2024  1292.000  2009.000  57688.000  11847.000  195.000  3326.000  4058.000   \n",
       "\n",
       "          批发零售     住宿餐饮       金融       房地产      租赁商务      科学研究     水环公设施  \\\n",
       "1985     8.570    1.130    1.642    14.350     0.156     4.794    16.836   \n",
       "1986     9.097    1.235    2.235    13.688     0.177     5.103    19.175   \n",
       "1987     9.777    1.364    2.919    13.088     0.201     5.499    21.980   \n",
       "1988    10.151    1.454    3.556    11.941     0.220     5.725    24.215   \n",
       "1989    10.733    1.577    4.305    10.920     0.244     6.069    27.047   \n",
       "1990    11.006    1.603    4.567     4.552     0.246     6.365    31.106   \n",
       "1991    16.966    2.294    5.354     7.943     0.327     6.588    39.827   \n",
       "1992    33.277    3.997    8.407    14.721     0.491     8.238    55.354   \n",
       "1993    43.625    5.918   15.306    32.347     0.846    11.169    82.197   \n",
       "1994    60.391    8.605   24.383    80.296     1.294    13.392   121.800   \n",
       "1995    60.677    9.513   32.695    47.724     1.559    17.788   153.057   \n",
       "1996    60.762   10.740   35.019    36.185     1.923    16.919   194.593   \n",
       "1997    61.628   12.714   35.553    36.470     2.494    16.974   244.855   \n",
       "1998    59.183   14.049   31.810    39.940     2.944    16.265   300.405   \n",
       "1999    52.090   14.760   25.292    36.920     3.306    17.688   344.149   \n",
       "2000    58.948   18.391   19.469    32.724     4.244    22.239   427.839   \n",
       "2001    62.645   20.177   18.156    32.996     4.700    24.719   442.863   \n",
       "2002    70.467   25.084   12.428    38.273     5.998    26.410   559.529   \n",
       "2003   105.000   50.000   38.000   219.000    31.000    62.000   150.000   \n",
       "2004   160.000   69.000   42.000   267.000    46.000    80.000   158.000   \n",
       "2005   223.000   91.000   35.000   307.000    53.000    90.000   184.000   \n",
       "2006   259.000  128.000   48.000   349.000    60.000   116.000   255.000   \n",
       "2007   329.000  168.000   64.000   430.000    85.000   129.000   294.000   \n",
       "2008   495.000  236.000  102.000   554.000   139.000   169.000   414.000   \n",
       "2009   728.000  314.000  108.000   579.000   227.000   235.000   590.000   \n",
       "2010   828.000  339.000  121.000   713.000   303.000   276.000   763.000   \n",
       "2011   950.000  362.000  123.000   980.000   369.000   263.000   839.000   \n",
       "2012  1153.000  459.000  138.000  1266.000   388.000   414.000  1069.000   \n",
       "2013  1350.000  459.000  148.000  1372.000   474.000   520.000  1292.000   \n",
       "2014  1576.000  415.000  155.000  1360.000   823.000   663.000  1411.000   \n",
       "2015  1993.000  421.000  129.000  1216.000   910.000   678.000  1610.000   \n",
       "2016  1981.000  370.000  146.000  1415.000  1332.000   714.000  2001.000   \n",
       "2017  1834.000  388.000   99.000  1526.000  1385.000   846.000  2458.000   \n",
       "2018  1394.000  389.000  183.000  1637.000  1275.000   922.000  2684.000   \n",
       "2019  1255.000  371.000  188.000  1795.000  1431.000   994.000  2622.000   \n",
       "2020   677.000  213.000  101.000  1439.000  1181.000   962.000  1969.000   \n",
       "2021   414.000  157.000  156.000  1288.000  1121.000  1045.000  1114.000   \n",
       "2022   402.000  156.000  163.000  1105.000   842.000  1172.000  1069.000   \n",
       "2023   383.000  215.000  213.000  1020.000   960.000  1275.000   869.000   \n",
       "2024   446.000  246.000  187.000   741.000  1320.000  1661.000  1004.000   \n",
       "\n",
       "         居民服务       教育     卫生与社会      文体娱     公共管理  \n",
       "1985   11.761   15.350     3.925    4.172   11.428  \n",
       "1986   16.230   17.260     4.352    4.670   12.522  \n",
       "1987   21.381   19.565     4.873    5.273   13.871  \n",
       "1988   26.200   21.346     5.258    5.733   14.821  \n",
       "1989   31.845   23.640     5.766    6.329   16.105  \n",
       "1990   31.713   26.481     7.880    7.570   18.797  \n",
       "1991   17.349   29.017     6.900    7.729   24.992  \n",
       "1992   54.694   33.709     8.775    9.349   36.973  \n",
       "1993   30.517   40.054    11.220   11.625   69.204  \n",
       "1994   35.484   56.649    17.543   17.123   95.587  \n",
       "1995   44.292   78.408    20.195   22.041  123.505  \n",
       "1996   50.134   92.502    23.424   25.936  150.527  \n",
       "1997   56.162  112.446    27.286   31.246  178.275  \n",
       "1998   47.458  112.689    29.213   32.375  190.499  \n",
       "1999   43.627  121.295    29.285   34.204  200.967  \n",
       "2000   65.536  151.560    34.757   42.188  189.427  \n",
       "2001   68.090  159.009    38.407   45.172  197.071  \n",
       "2002   66.340  188.646    47.546   54.673  256.913  \n",
       "2003    7.000  113.000   124.000   77.000  192.000  \n",
       "2004   36.000  133.000   303.000   85.000  281.000  \n",
       "2005   24.000  165.000   160.000   94.000  361.000  \n",
       "2006   37.000  183.000   163.000  113.000  402.000  \n",
       "2007   43.000  193.000   194.000  126.000  382.000  \n",
       "2008   67.000  234.000   242.000  165.000  461.000  \n",
       "2009   96.000  262.000   295.000  230.000  432.000  \n",
       "2010   93.000  274.000   335.000  272.000  437.000  \n",
       "2011  134.000  243.000   310.000  285.000  391.000  \n",
       "2012  198.000  303.000   360.000  353.000  408.000  \n",
       "2013  201.000  286.000   393.000  374.000  306.000  \n",
       "2014  198.000  362.000   495.000  426.000  368.000  \n",
       "2015  243.000  450.000   516.000  446.000  382.000  \n",
       "2016  246.000  442.000   571.000  489.000  408.000  \n",
       "2017  263.000  517.000   654.000  500.000  403.000  \n",
       "2018  215.000  550.000   768.000  621.000  282.000  \n",
       "2019  210.000  564.000   865.000  619.000  270.000  \n",
       "2020  125.000  473.000  1155.000  520.000  236.000  \n",
       "2021   96.000  572.000  1314.000  380.000  100.000  \n",
       "2022   89.000  548.000  1391.000  322.000   85.000  \n",
       "2023   86.000  661.000  1586.000  243.000   80.000  \n",
       "2024  107.000  744.000  1353.000  251.000  187.000  "
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "equipment_1985_2002 = pd.read_excel('data/kdata/计算得到1985-2002年19行业固定资产投资完成额.xlsx', \n",
    "                                    index_col=0, sheet_name='设备工器具购置')\n",
    "equipment_ = pd.concat([equipment_1985_2002, equipment_2024], axis=0)\n",
    "equipment_.round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "265ebc86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(40, 19)"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_.shape\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "71336cff",
   "metadata": {},
   "source": [
    "# 永续盘存"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "42dbc6a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "农林牧渔     0.894590\n",
       "采矿       0.739603\n",
       "制造       0.626706\n",
       "电热燃水     0.655347\n",
       "建筑       0.823237\n",
       "交通运输     0.887548\n",
       "信息软件     0.553518\n",
       "批发零售     0.840769\n",
       "住宿餐饮     0.903676\n",
       "金融       0.733459\n",
       "房地产      0.980742\n",
       "租赁商务     0.887622\n",
       "科学研究     0.796912\n",
       "水环公设施    0.962513\n",
       "居民服务     0.867101\n",
       "教育       0.931910\n",
       "卫生与社会    0.837865\n",
       "文体娱      0.920356\n",
       "公共管理     0.906093\n",
       "dtype: float64"
      ]
     },
     "execution_count": 166,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 计算比例\n",
    "build_2024_sum = build_2024.sum()\n",
    "equipment_2024_sum = equipment_2024.sum()\n",
    "build_2024_ratio = build_2024_sum / (build_2024_sum + equipment_2024_sum)\n",
    "equipment_2024_ratio = equipment_2024_sum / (build_2024_sum + equipment_2024_sum)\n",
    "build_2024_ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "e96c7bb5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>建筑安装工程</th>\n",
       "      <td>0.89459</td>\n",
       "      <td>0.739603</td>\n",
       "      <td>0.626706</td>\n",
       "      <td>0.655347</td>\n",
       "      <td>0.823237</td>\n",
       "      <td>0.887548</td>\n",
       "      <td>0.553518</td>\n",
       "      <td>0.840769</td>\n",
       "      <td>0.903676</td>\n",
       "      <td>0.733459</td>\n",
       "      <td>0.980742</td>\n",
       "      <td>0.887622</td>\n",
       "      <td>0.796912</td>\n",
       "      <td>0.962513</td>\n",
       "      <td>0.867101</td>\n",
       "      <td>0.93191</td>\n",
       "      <td>0.837865</td>\n",
       "      <td>0.920356</td>\n",
       "      <td>0.906093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>设备工器具</th>\n",
       "      <td>0.10541</td>\n",
       "      <td>0.260397</td>\n",
       "      <td>0.373294</td>\n",
       "      <td>0.344653</td>\n",
       "      <td>0.176763</td>\n",
       "      <td>0.112452</td>\n",
       "      <td>0.446482</td>\n",
       "      <td>0.159231</td>\n",
       "      <td>0.096324</td>\n",
       "      <td>0.266541</td>\n",
       "      <td>0.019258</td>\n",
       "      <td>0.112378</td>\n",
       "      <td>0.203088</td>\n",
       "      <td>0.037487</td>\n",
       "      <td>0.132899</td>\n",
       "      <td>0.06809</td>\n",
       "      <td>0.162135</td>\n",
       "      <td>0.079644</td>\n",
       "      <td>0.093907</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           农林牧渔        采矿        制造      电热燃水        建筑      交通运输      信息软件  \\\n",
       "建筑安装工程  0.89459  0.739603  0.626706  0.655347  0.823237  0.887548  0.553518   \n",
       "设备工器具   0.10541  0.260397  0.373294  0.344653  0.176763  0.112452  0.446482   \n",
       "\n",
       "            批发零售      住宿餐饮        金融       房地产      租赁商务      科学研究     水环公设施  \\\n",
       "建筑安装工程  0.840769  0.903676  0.733459  0.980742  0.887622  0.796912  0.962513   \n",
       "设备工器具   0.159231  0.096324  0.266541  0.019258  0.112378  0.203088  0.037487   \n",
       "\n",
       "            居民服务       教育     卫生与社会       文体娱      公共管理  \n",
       "建筑安装工程  0.867101  0.93191  0.837865  0.920356  0.906093  \n",
       "设备工器具   0.132899  0.06809  0.162135  0.079644  0.093907  "
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ratio_all = pd.DataFrame({\n",
    "    '建筑安装工程': build_2024_ratio,\n",
    "    '设备工器具': equipment_2024_ratio\n",
    "}).T\n",
    "df_ratio_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "a17ff7ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>8917.532481</td>\n",
       "      <td>7374.781349</td>\n",
       "      <td>48781.103618</td>\n",
       "      <td>11248.954965</td>\n",
       "      <td>8299.196599</td>\n",
       "      <td>22697.849747</td>\n",
       "      <td>9086.696004</td>\n",
       "      <td>8815.796068</td>\n",
       "      <td>3436.622117</td>\n",
       "      <td>5730.420548</td>\n",
       "      <td>36063.152216</td>\n",
       "      <td>2452.709405</td>\n",
       "      <td>2134.175651</td>\n",
       "      <td>1704.641125</td>\n",
       "      <td>3751.036383</td>\n",
       "      <td>5680.34002</td>\n",
       "      <td>3408.36793</td>\n",
       "      <td>1030.655133</td>\n",
       "      <td>9764.307287</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             农林牧渔           采矿            制造          电热燃水           建筑  \\\n",
       "2002  8917.532481  7374.781349  48781.103618  11248.954965  8299.196599   \n",
       "\n",
       "              交通运输         信息软件         批发零售         住宿餐饮           金融  \\\n",
       "2002  22697.849747  9086.696004  8815.796068  3436.622117  5730.420548   \n",
       "\n",
       "               房地产         租赁商务         科学研究        水环公设施         居民服务  \\\n",
       "2002  36063.152216  2452.709405  2134.175651  1704.641125  3751.036383   \n",
       "\n",
       "              教育       卫生与社会          文体娱         公共管理  \n",
       "2002  5680.34002  3408.36793  1030.655133  9764.307287  "
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_stock_2002 = pd.read_excel(\n",
    "    'data/kdata/2022年初始资本存量计算.xlsx', \n",
    "    sheet_name='输出', index_col=0)\n",
    "df_stock_2002.index = [2002]\n",
    "df_stock_2002"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "1f318cb2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2002</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>农林牧渔</th>\n",
       "      <td>7977.536963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>采矿</th>\n",
       "      <td>5454.407742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>制造</th>\n",
       "      <td>30571.419745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>电热燃水</th>\n",
       "      <td>7371.973769</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>建筑</th>\n",
       "      <td>6832.209074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>交通运输</th>\n",
       "      <td>20145.435853</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>信息软件</th>\n",
       "      <td>5029.645398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>批发零售</th>\n",
       "      <td>7412.044661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>住宿餐饮</th>\n",
       "      <td>3105.593574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>金融</th>\n",
       "      <td>4203.028423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>房地产</th>\n",
       "      <td>35368.658310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>租赁商务</th>\n",
       "      <td>2177.078951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>科学研究</th>\n",
       "      <td>1700.750740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>水环公设施</th>\n",
       "      <td>1640.739579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>居民服务</th>\n",
       "      <td>3252.528005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>教育</th>\n",
       "      <td>5293.564814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>卫生与社会</th>\n",
       "      <td>2855.753329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>文体娱</th>\n",
       "      <td>948.569531</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>公共管理</th>\n",
       "      <td>8847.369173</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               2002\n",
       "农林牧渔    7977.536963\n",
       "采矿      5454.407742\n",
       "制造     30571.419745\n",
       "电热燃水    7371.973769\n",
       "建筑      6832.209074\n",
       "交通运输   20145.435853\n",
       "信息软件    5029.645398\n",
       "批发零售    7412.044661\n",
       "住宿餐饮    3105.593574\n",
       "金融      4203.028423\n",
       "房地产    35368.658310\n",
       "租赁商务    2177.078951\n",
       "科学研究    1700.750740\n",
       "水环公设施   1640.739579\n",
       "居民服务    3252.528005\n",
       "教育      5293.564814\n",
       "卫生与社会   2855.753329\n",
       "文体娱      948.569531\n",
       "公共管理    8847.369173"
      ]
     },
     "execution_count": 169,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "se_build_ratio = df_ratio_all.iloc[0,:]\n",
    "se_equipment_ratio = df_ratio_all.iloc[1,:]\n",
    "se_build_ratio.astype(float)\n",
    "df_stock_2002.astype(float)\n",
    "se_stock_2002 = df_stock_2002.iloc[0,:]\n",
    "# se_stock_2002 * se_build_ratio\n",
    "build_df_all = pd.DataFrame(se_stock_2002 * se_build_ratio)\n",
    "equipment_df_all = pd.DataFrame(se_stock_2002 * se_equipment_ratio)\n",
    "build_df_all.columns = [2002]\n",
    "equipment_df_all.columns = [2002]\n",
    "build_df_all\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "b8401e67",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2002</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>农林牧渔</th>\n",
       "      <td>939.995518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>采矿</th>\n",
       "      <td>1920.373607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>制造</th>\n",
       "      <td>18209.683873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>电热燃水</th>\n",
       "      <td>3876.981196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>建筑</th>\n",
       "      <td>1466.987525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>交通运输</th>\n",
       "      <td>2552.413894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>信息软件</th>\n",
       "      <td>4057.050606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>批发零售</th>\n",
       "      <td>1403.751407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>住宿餐饮</th>\n",
       "      <td>331.028543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>金融</th>\n",
       "      <td>1527.392125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>房地产</th>\n",
       "      <td>694.493906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>租赁商务</th>\n",
       "      <td>275.630453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>科学研究</th>\n",
       "      <td>433.424911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>水环公设施</th>\n",
       "      <td>63.901546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>居民服务</th>\n",
       "      <td>498.508377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>教育</th>\n",
       "      <td>386.775206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>卫生与社会</th>\n",
       "      <td>552.614601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>文体娱</th>\n",
       "      <td>82.085603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>公共管理</th>\n",
       "      <td>916.938114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               2002\n",
       "农林牧渔     939.995518\n",
       "采矿      1920.373607\n",
       "制造     18209.683873\n",
       "电热燃水    3876.981196\n",
       "建筑      1466.987525\n",
       "交通运输    2552.413894\n",
       "信息软件    4057.050606\n",
       "批发零售    1403.751407\n",
       "住宿餐饮     331.028543\n",
       "金融      1527.392125\n",
       "房地产      694.493906\n",
       "租赁商务     275.630453\n",
       "科学研究     433.424911\n",
       "水环公设施     63.901546\n",
       "居民服务     498.508377\n",
       "教育       386.775206\n",
       "卫生与社会    552.614601\n",
       "文体娱       82.085603\n",
       "公共管理     916.938114"
      ]
     },
     "execution_count": 170,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "equipment_df_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "56286c0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 计算2002年至2023年的建筑安装工程资本存量\n",
    "# 折旧率\n",
    "\n",
    "depreciation_rate_build = calculate_depreciation_rate_multiple_methods(\n",
    "    55, 0.05, method='geometric'\n",
    "    )\n",
    "    \n",
    "for year in range(2003, 2025):\n",
    "    df_build_last_year = build_df_all[year-1]\n",
    "    keeper_build = df_build_last_year * (1 -depreciation_rate_build)\n",
    "    adder_build = build_2024.loc[year,:]\n",
    "    new_year_build = keeper_build + adder_build\n",
    "    build_df_all[year] = new_year_build\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "26022d9c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>7977.5</td>\n",
       "      <td>5454.4</td>\n",
       "      <td>30571.4</td>\n",
       "      <td>7372.0</td>\n",
       "      <td>6832.2</td>\n",
       "      <td>20145.4</td>\n",
       "      <td>5029.6</td>\n",
       "      <td>7412.0</td>\n",
       "      <td>3105.6</td>\n",
       "      <td>4203.0</td>\n",
       "      <td>35368.7</td>\n",
       "      <td>2177.1</td>\n",
       "      <td>1700.8</td>\n",
       "      <td>1640.7</td>\n",
       "      <td>3252.5</td>\n",
       "      <td>5293.6</td>\n",
       "      <td>2855.8</td>\n",
       "      <td>948.6</td>\n",
       "      <td>8847.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>7993.6</td>\n",
       "      <td>6638.3</td>\n",
       "      <td>35374.8</td>\n",
       "      <td>9760.2</td>\n",
       "      <td>7036.0</td>\n",
       "      <td>25022.5</td>\n",
       "      <td>5650.0</td>\n",
       "      <td>7849.1</td>\n",
       "      <td>3268.0</td>\n",
       "      <td>4053.2</td>\n",
       "      <td>44237.7</td>\n",
       "      <td>2376.7</td>\n",
       "      <td>1875.6</td>\n",
       "      <td>5685.8</td>\n",
       "      <td>3149.1</td>\n",
       "      <td>6701.9</td>\n",
       "      <td>3050.4</td>\n",
       "      <td>1380.3</td>\n",
       "      <td>10461.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>8016.9</td>\n",
       "      <td>8084.4</td>\n",
       "      <td>41668.5</td>\n",
       "      <td>12845.8</td>\n",
       "      <td>7187.0</td>\n",
       "      <td>30570.0</td>\n",
       "      <td>6177.5</td>\n",
       "      <td>8463.0</td>\n",
       "      <td>3513.7</td>\n",
       "      <td>3909.4</td>\n",
       "      <td>54747.6</td>\n",
       "      <td>2578.7</td>\n",
       "      <td>2032.2</td>\n",
       "      <td>9904.4</td>\n",
       "      <td>3067.2</td>\n",
       "      <td>8264.7</td>\n",
       "      <td>5034.7</td>\n",
       "      <td>1816.1</td>\n",
       "      <td>12022.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>8175.9</td>\n",
       "      <td>10086.8</td>\n",
       "      <td>50447.6</td>\n",
       "      <td>16608.8</td>\n",
       "      <td>7374.0</td>\n",
       "      <td>36696.5</td>\n",
       "      <td>6610.0</td>\n",
       "      <td>9348.4</td>\n",
       "      <td>3918.5</td>\n",
       "      <td>3779.1</td>\n",
       "      <td>66029.4</td>\n",
       "      <td>2834.0</td>\n",
       "      <td>2249.4</td>\n",
       "      <td>14687.3</td>\n",
       "      <td>3015.6</td>\n",
       "      <td>9749.6</td>\n",
       "      <td>5249.8</td>\n",
       "      <td>2262.8</td>\n",
       "      <td>13573.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>8482.5</td>\n",
       "      <td>12489.1</td>\n",
       "      <td>60955.4</td>\n",
       "      <td>20304.4</td>\n",
       "      <td>7612.1</td>\n",
       "      <td>44005.2</td>\n",
       "      <td>7043.6</td>\n",
       "      <td>10346.8</td>\n",
       "      <td>4467.7</td>\n",
       "      <td>3647.8</td>\n",
       "      <td>79223.1</td>\n",
       "      <td>3177.7</td>\n",
       "      <td>2446.2</td>\n",
       "      <td>19719.7</td>\n",
       "      <td>2995.7</td>\n",
       "      <td>11116.7</td>\n",
       "      <td>5515.5</td>\n",
       "      <td>2811.9</td>\n",
       "      <td>15045.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>8968.8</td>\n",
       "      <td>15508.0</td>\n",
       "      <td>75230.1</td>\n",
       "      <td>24045.0</td>\n",
       "      <td>7956.6</td>\n",
       "      <td>51432.4</td>\n",
       "      <td>7440.2</td>\n",
       "      <td>11651.3</td>\n",
       "      <td>5263.9</td>\n",
       "      <td>3535.4</td>\n",
       "      <td>96148.4</td>\n",
       "      <td>3639.3</td>\n",
       "      <td>2659.5</td>\n",
       "      <td>25663.4</td>\n",
       "      <td>3014.9</td>\n",
       "      <td>12407.4</td>\n",
       "      <td>5812.1</td>\n",
       "      <td>3548.8</td>\n",
       "      <td>16442.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>9899.4</td>\n",
       "      <td>19011.9</td>\n",
       "      <td>93116.0</td>\n",
       "      <td>28056.4</td>\n",
       "      <td>8349.8</td>\n",
       "      <td>59488.9</td>\n",
       "      <td>7972.8</td>\n",
       "      <td>13322.7</td>\n",
       "      <td>6272.9</td>\n",
       "      <td>3464.0</td>\n",
       "      <td>117029.5</td>\n",
       "      <td>4339.4</td>\n",
       "      <td>2979.5</td>\n",
       "      <td>33277.9</td>\n",
       "      <td>3066.1</td>\n",
       "      <td>13647.7</td>\n",
       "      <td>6235.0</td>\n",
       "      <td>4429.7</td>\n",
       "      <td>17990.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>11364.6</td>\n",
       "      <td>22612.1</td>\n",
       "      <td>114226.9</td>\n",
       "      <td>32932.1</td>\n",
       "      <td>8961.2</td>\n",
       "      <td>71710.3</td>\n",
       "      <td>8644.2</td>\n",
       "      <td>15621.4</td>\n",
       "      <td>7545.3</td>\n",
       "      <td>3455.4</td>\n",
       "      <td>140702.6</td>\n",
       "      <td>5348.3</td>\n",
       "      <td>3465.6</td>\n",
       "      <td>43790.8</td>\n",
       "      <td>3222.6</td>\n",
       "      <td>15388.2</td>\n",
       "      <td>7070.5</td>\n",
       "      <td>5659.9</td>\n",
       "      <td>19969.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>13001.2</td>\n",
       "      <td>26576.4</td>\n",
       "      <td>140332.6</td>\n",
       "      <td>37659.3</td>\n",
       "      <td>9965.1</td>\n",
       "      <td>85776.9</td>\n",
       "      <td>9107.9</td>\n",
       "      <td>18005.3</td>\n",
       "      <td>9102.3</td>\n",
       "      <td>3509.2</td>\n",
       "      <td>170161.8</td>\n",
       "      <td>6600.8</td>\n",
       "      <td>3961.9</td>\n",
       "      <td>56467.4</td>\n",
       "      <td>3502.7</td>\n",
       "      <td>17332.5</td>\n",
       "      <td>7976.7</td>\n",
       "      <td>7088.8</td>\n",
       "      <td>22205.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>16144.9</td>\n",
       "      <td>31104.6</td>\n",
       "      <td>175769.4</td>\n",
       "      <td>42077.9</td>\n",
       "      <td>11527.9</td>\n",
       "      <td>98015.8</td>\n",
       "      <td>9559.1</td>\n",
       "      <td>21387.8</td>\n",
       "      <td>11131.8</td>\n",
       "      <td>3663.2</td>\n",
       "      <td>208030.4</td>\n",
       "      <td>8227.9</td>\n",
       "      <td>4678.8</td>\n",
       "      <td>69455.0</td>\n",
       "      <td>4006.0</td>\n",
       "      <td>19042.6</td>\n",
       "      <td>9018.8</td>\n",
       "      <td>8641.1</td>\n",
       "      <td>24862.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>19967.1</td>\n",
       "      <td>35745.7</td>\n",
       "      <td>215505.7</td>\n",
       "      <td>46636.3</td>\n",
       "      <td>13184.8</td>\n",
       "      <td>109405.9</td>\n",
       "      <td>10159.4</td>\n",
       "      <td>25588.1</td>\n",
       "      <td>13485.7</td>\n",
       "      <td>3891.0</td>\n",
       "      <td>250368.5</td>\n",
       "      <td>10402.7</td>\n",
       "      <td>5648.8</td>\n",
       "      <td>83454.1</td>\n",
       "      <td>4715.7</td>\n",
       "      <td>20921.2</td>\n",
       "      <td>10007.7</td>\n",
       "      <td>10627.0</td>\n",
       "      <td>27313.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>24581.6</td>\n",
       "      <td>40529.8</td>\n",
       "      <td>257998.5</td>\n",
       "      <td>51725.1</td>\n",
       "      <td>14390.8</td>\n",
       "      <td>121614.1</td>\n",
       "      <td>10788.8</td>\n",
       "      <td>30684.6</td>\n",
       "      <td>16050.8</td>\n",
       "      <td>4300.7</td>\n",
       "      <td>297203.2</td>\n",
       "      <td>12903.3</td>\n",
       "      <td>6774.4</td>\n",
       "      <td>100583.1</td>\n",
       "      <td>5514.7</td>\n",
       "      <td>22951.1</td>\n",
       "      <td>11121.2</td>\n",
       "      <td>12853.6</td>\n",
       "      <td>29319.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>30109.5</td>\n",
       "      <td>44661.2</td>\n",
       "      <td>302828.7</td>\n",
       "      <td>57230.1</td>\n",
       "      <td>15678.0</td>\n",
       "      <td>135386.2</td>\n",
       "      <td>11650.9</td>\n",
       "      <td>36557.0</td>\n",
       "      <td>18401.9</td>\n",
       "      <td>4718.7</td>\n",
       "      <td>342896.1</td>\n",
       "      <td>15923.3</td>\n",
       "      <td>8223.3</td>\n",
       "      <td>120144.1</td>\n",
       "      <td>6362.4</td>\n",
       "      <td>25301.5</td>\n",
       "      <td>12415.6</td>\n",
       "      <td>15246.2</td>\n",
       "      <td>31623.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>36920.4</td>\n",
       "      <td>47578.7</td>\n",
       "      <td>345972.4</td>\n",
       "      <td>63405.3</td>\n",
       "      <td>17134.9</td>\n",
       "      <td>149906.3</td>\n",
       "      <td>12899.3</td>\n",
       "      <td>42863.1</td>\n",
       "      <td>20539.4</td>\n",
       "      <td>5058.6</td>\n",
       "      <td>383225.8</td>\n",
       "      <td>19291.1</td>\n",
       "      <td>9719.3</td>\n",
       "      <td>141687.2</td>\n",
       "      <td>7233.1</td>\n",
       "      <td>27782.2</td>\n",
       "      <td>14088.5</td>\n",
       "      <td>17594.0</td>\n",
       "      <td>33874.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>45053.2</td>\n",
       "      <td>49194.5</td>\n",
       "      <td>390387.1</td>\n",
       "      <td>70445.1</td>\n",
       "      <td>18442.5</td>\n",
       "      <td>165870.6</td>\n",
       "      <td>14327.5</td>\n",
       "      <td>48461.8</td>\n",
       "      <td>22313.6</td>\n",
       "      <td>5356.4</td>\n",
       "      <td>424544.6</td>\n",
       "      <td>23567.5</td>\n",
       "      <td>11497.1</td>\n",
       "      <td>168048.2</td>\n",
       "      <td>8070.6</td>\n",
       "      <td>30903.4</td>\n",
       "      <td>16220.6</td>\n",
       "      <td>20226.4</td>\n",
       "      <td>36125.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>54644.9</td>\n",
       "      <td>50606.6</td>\n",
       "      <td>438987.2</td>\n",
       "      <td>78251.7</td>\n",
       "      <td>19302.9</td>\n",
       "      <td>186548.6</td>\n",
       "      <td>15997.9</td>\n",
       "      <td>53822.8</td>\n",
       "      <td>24325.7</td>\n",
       "      <td>5602.5</td>\n",
       "      <td>467368.1</td>\n",
       "      <td>28422.2</td>\n",
       "      <td>13530.6</td>\n",
       "      <td>202141.8</td>\n",
       "      <td>8953.8</td>\n",
       "      <td>35156.2</td>\n",
       "      <td>19017.8</td>\n",
       "      <td>23590.1</td>\n",
       "      <td>38550.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>66493.1</td>\n",
       "      <td>52509.9</td>\n",
       "      <td>499875.1</td>\n",
       "      <td>86293.5</td>\n",
       "      <td>19995.6</td>\n",
       "      <td>210311.5</td>\n",
       "      <td>17773.9</td>\n",
       "      <td>57909.6</td>\n",
       "      <td>26321.2</td>\n",
       "      <td>5742.5</td>\n",
       "      <td>511592.4</td>\n",
       "      <td>34640.5</td>\n",
       "      <td>16080.4</td>\n",
       "      <td>240574.0</td>\n",
       "      <td>9760.2</td>\n",
       "      <td>40319.5</td>\n",
       "      <td>22300.6</td>\n",
       "      <td>28261.6</td>\n",
       "      <td>40600.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>78529.2</td>\n",
       "      <td>55688.3</td>\n",
       "      <td>563148.2</td>\n",
       "      <td>95037.0</td>\n",
       "      <td>19183.6</td>\n",
       "      <td>235962.6</td>\n",
       "      <td>19809.7</td>\n",
       "      <td>60715.8</td>\n",
       "      <td>28310.9</td>\n",
       "      <td>5889.1</td>\n",
       "      <td>560853.3</td>\n",
       "      <td>42097.1</td>\n",
       "      <td>19144.9</td>\n",
       "      <td>281414.9</td>\n",
       "      <td>10428.8</td>\n",
       "      <td>46745.2</td>\n",
       "      <td>25766.4</td>\n",
       "      <td>33704.4</td>\n",
       "      <td>41966.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>93609.3</td>\n",
       "      <td>57986.2</td>\n",
       "      <td>624414.1</td>\n",
       "      <td>105587.0</td>\n",
       "      <td>18459.7</td>\n",
       "      <td>261323.0</td>\n",
       "      <td>22206.5</td>\n",
       "      <td>62135.2</td>\n",
       "      <td>30093.1</td>\n",
       "      <td>5945.9</td>\n",
       "      <td>611253.9</td>\n",
       "      <td>49848.5</td>\n",
       "      <td>22188.0</td>\n",
       "      <td>320625.8</td>\n",
       "      <td>11064.9</td>\n",
       "      <td>54006.2</td>\n",
       "      <td>30195.5</td>\n",
       "      <td>39073.7</td>\n",
       "      <td>43026.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>112135.0</td>\n",
       "      <td>60901.3</td>\n",
       "      <td>706592.2</td>\n",
       "      <td>116706.7</td>\n",
       "      <td>17799.1</td>\n",
       "      <td>287571.0</td>\n",
       "      <td>25286.3</td>\n",
       "      <td>63656.3</td>\n",
       "      <td>32205.8</td>\n",
       "      <td>6011.7</td>\n",
       "      <td>668106.7</td>\n",
       "      <td>59277.0</td>\n",
       "      <td>25952.8</td>\n",
       "      <td>359939.1</td>\n",
       "      <td>11636.4</td>\n",
       "      <td>62415.2</td>\n",
       "      <td>35949.8</td>\n",
       "      <td>44832.4</td>\n",
       "      <td>42872.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>130935.6</td>\n",
       "      <td>64491.9</td>\n",
       "      <td>801936.0</td>\n",
       "      <td>129439.0</td>\n",
       "      <td>17122.6</td>\n",
       "      <td>313063.6</td>\n",
       "      <td>28549.9</td>\n",
       "      <td>65261.8</td>\n",
       "      <td>34448.6</td>\n",
       "      <td>6082.0</td>\n",
       "      <td>711120.7</td>\n",
       "      <td>69877.7</td>\n",
       "      <td>30541.0</td>\n",
       "      <td>400399.4</td>\n",
       "      <td>12400.5</td>\n",
       "      <td>70448.5</td>\n",
       "      <td>43384.1</td>\n",
       "      <td>50523.8</td>\n",
       "      <td>43688.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>148245.5</td>\n",
       "      <td>68477.1</td>\n",
       "      <td>905859.6</td>\n",
       "      <td>144879.3</td>\n",
       "      <td>16583.9</td>\n",
       "      <td>338808.7</td>\n",
       "      <td>32159.4</td>\n",
       "      <td>66707.2</td>\n",
       "      <td>36899.4</td>\n",
       "      <td>6158.6</td>\n",
       "      <td>743307.4</td>\n",
       "      <td>81558.4</td>\n",
       "      <td>35982.0</td>\n",
       "      <td>437525.8</td>\n",
       "      <td>13304.1</td>\n",
       "      <td>78188.0</td>\n",
       "      <td>49637.3</td>\n",
       "      <td>56031.4</td>\n",
       "      <td>43214.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <td>167712.9</td>\n",
       "      <td>72341.0</td>\n",
       "      <td>1015507.0</td>\n",
       "      <td>164455.1</td>\n",
       "      <td>15998.7</td>\n",
       "      <td>363297.1</td>\n",
       "      <td>35600.6</td>\n",
       "      <td>68282.0</td>\n",
       "      <td>40409.3</td>\n",
       "      <td>6191.1</td>\n",
       "      <td>764072.9</td>\n",
       "      <td>92791.9</td>\n",
       "      <td>41465.6</td>\n",
       "      <td>472608.1</td>\n",
       "      <td>14098.9</td>\n",
       "      <td>84894.2</td>\n",
       "      <td>54418.9</td>\n",
       "      <td>61000.2</td>\n",
       "      <td>42453.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          农林牧渔       采矿         制造      电热燃水       建筑      交通运输     信息软件  \\\n",
       "2002    7977.5   5454.4    30571.4    7372.0   6832.2   20145.4   5029.6   \n",
       "2003    7993.6   6638.3    35374.8    9760.2   7036.0   25022.5   5650.0   \n",
       "2004    8016.9   8084.4    41668.5   12845.8   7187.0   30570.0   6177.5   \n",
       "2005    8175.9  10086.8    50447.6   16608.8   7374.0   36696.5   6610.0   \n",
       "2006    8482.5  12489.1    60955.4   20304.4   7612.1   44005.2   7043.6   \n",
       "2007    8968.8  15508.0    75230.1   24045.0   7956.6   51432.4   7440.2   \n",
       "2008    9899.4  19011.9    93116.0   28056.4   8349.8   59488.9   7972.8   \n",
       "2009   11364.6  22612.1   114226.9   32932.1   8961.2   71710.3   8644.2   \n",
       "2010   13001.2  26576.4   140332.6   37659.3   9965.1   85776.9   9107.9   \n",
       "2011   16144.9  31104.6   175769.4   42077.9  11527.9   98015.8   9559.1   \n",
       "2012   19967.1  35745.7   215505.7   46636.3  13184.8  109405.9  10159.4   \n",
       "2013   24581.6  40529.8   257998.5   51725.1  14390.8  121614.1  10788.8   \n",
       "2014   30109.5  44661.2   302828.7   57230.1  15678.0  135386.2  11650.9   \n",
       "2015   36920.4  47578.7   345972.4   63405.3  17134.9  149906.3  12899.3   \n",
       "2016   45053.2  49194.5   390387.1   70445.1  18442.5  165870.6  14327.5   \n",
       "2017   54644.9  50606.6   438987.2   78251.7  19302.9  186548.6  15997.9   \n",
       "2018   66493.1  52509.9   499875.1   86293.5  19995.6  210311.5  17773.9   \n",
       "2019   78529.2  55688.3   563148.2   95037.0  19183.6  235962.6  19809.7   \n",
       "2020   93609.3  57986.2   624414.1  105587.0  18459.7  261323.0  22206.5   \n",
       "2021  112135.0  60901.3   706592.2  116706.7  17799.1  287571.0  25286.3   \n",
       "2022  130935.6  64491.9   801936.0  129439.0  17122.6  313063.6  28549.9   \n",
       "2023  148245.5  68477.1   905859.6  144879.3  16583.9  338808.7  32159.4   \n",
       "2024  167712.9  72341.0  1015507.0  164455.1  15998.7  363297.1  35600.6   \n",
       "\n",
       "         批发零售     住宿餐饮      金融       房地产     租赁商务     科学研究     水环公设施     居民服务  \\\n",
       "2002   7412.0   3105.6  4203.0   35368.7   2177.1   1700.8    1640.7   3252.5   \n",
       "2003   7849.1   3268.0  4053.2   44237.7   2376.7   1875.6    5685.8   3149.1   \n",
       "2004   8463.0   3513.7  3909.4   54747.6   2578.7   2032.2    9904.4   3067.2   \n",
       "2005   9348.4   3918.5  3779.1   66029.4   2834.0   2249.4   14687.3   3015.6   \n",
       "2006  10346.8   4467.7  3647.8   79223.1   3177.7   2446.2   19719.7   2995.7   \n",
       "2007  11651.3   5263.9  3535.4   96148.4   3639.3   2659.5   25663.4   3014.9   \n",
       "2008  13322.7   6272.9  3464.0  117029.5   4339.4   2979.5   33277.9   3066.1   \n",
       "2009  15621.4   7545.3  3455.4  140702.6   5348.3   3465.6   43790.8   3222.6   \n",
       "2010  18005.3   9102.3  3509.2  170161.8   6600.8   3961.9   56467.4   3502.7   \n",
       "2011  21387.8  11131.8  3663.2  208030.4   8227.9   4678.8   69455.0   4006.0   \n",
       "2012  25588.1  13485.7  3891.0  250368.5  10402.7   5648.8   83454.1   4715.7   \n",
       "2013  30684.6  16050.8  4300.7  297203.2  12903.3   6774.4  100583.1   5514.7   \n",
       "2014  36557.0  18401.9  4718.7  342896.1  15923.3   8223.3  120144.1   6362.4   \n",
       "2015  42863.1  20539.4  5058.6  383225.8  19291.1   9719.3  141687.2   7233.1   \n",
       "2016  48461.8  22313.6  5356.4  424544.6  23567.5  11497.1  168048.2   8070.6   \n",
       "2017  53822.8  24325.7  5602.5  467368.1  28422.2  13530.6  202141.8   8953.8   \n",
       "2018  57909.6  26321.2  5742.5  511592.4  34640.5  16080.4  240574.0   9760.2   \n",
       "2019  60715.8  28310.9  5889.1  560853.3  42097.1  19144.9  281414.9  10428.8   \n",
       "2020  62135.2  30093.1  5945.9  611253.9  49848.5  22188.0  320625.8  11064.9   \n",
       "2021  63656.3  32205.8  6011.7  668106.7  59277.0  25952.8  359939.1  11636.4   \n",
       "2022  65261.8  34448.6  6082.0  711120.7  69877.7  30541.0  400399.4  12400.5   \n",
       "2023  66707.2  36899.4  6158.6  743307.4  81558.4  35982.0  437525.8  13304.1   \n",
       "2024  68282.0  40409.3  6191.1  764072.9  92791.9  41465.6  472608.1  14098.9   \n",
       "\n",
       "           教育    卫生与社会      文体娱     公共管理  \n",
       "2002   5293.6   2855.8    948.6   8847.4  \n",
       "2003   6701.9   3050.4   1380.3  10461.4  \n",
       "2004   8264.7   5034.7   1816.1  12022.8  \n",
       "2005   9749.6   5249.8   2262.8  13573.5  \n",
       "2006  11116.7   5515.5   2811.9  15045.9  \n",
       "2007  12407.4   5812.1   3548.8  16442.3  \n",
       "2008  13647.7   6235.0   4429.7  17990.7  \n",
       "2009  15388.2   7070.5   5659.9  19969.0  \n",
       "2010  17332.5   7976.7   7088.8  22205.4  \n",
       "2011  19042.6   9018.8   8641.1  24862.3  \n",
       "2012  20921.2  10007.7  10627.0  27313.3  \n",
       "2013  22951.1  11121.2  12853.6  29319.4  \n",
       "2014  25301.5  12415.6  15246.2  31623.1  \n",
       "2015  27782.2  14088.5  17594.0  33874.8  \n",
       "2016  30903.4  16220.6  20226.4  36125.0  \n",
       "2017  35156.2  19017.8  23590.1  38550.0  \n",
       "2018  40319.5  22300.6  28261.6  40600.4  \n",
       "2019  46745.2  25766.4  33704.4  41966.2  \n",
       "2020  54006.2  30195.5  39073.7  43026.5  \n",
       "2021  62415.2  35949.8  44832.4  42872.6  \n",
       "2022  70448.5  43384.1  50523.8  43688.9  \n",
       "2023  78188.0  49637.3  56031.4  43214.9  \n",
       "2024  84894.2  54418.9  61000.2  42453.0  "
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "build_df_all.T.round(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "d658d2ad",
   "metadata": {},
   "outputs": [],
   "source": [
    "depreciation_rate_equipment = calculate_depreciation_rate_multiple_methods(\n",
    "    16, 0.05, method='geometric'\n",
    "    )\n",
    "for year in range(2003, 2025):\n",
    "    df_equipment_last_year = equipment_df_all[year-1]\n",
    "    keeper_equipment = df_equipment_last_year * (1 -depreciation_rate_equipment)\n",
    "    adder_equipment = equipment_2024.loc[year,:]\n",
    "    new_year_equipment = keeper_equipment + adder_equipment\n",
    "    equipment_df_all[year] = new_year_equipment\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e487e70",
   "metadata": {},
   "source": [
    "equipment_df_all.T.round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "9aa619c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>农林牧渔</th>\n",
       "      <th>采矿</th>\n",
       "      <th>制造</th>\n",
       "      <th>电热燃水</th>\n",
       "      <th>建筑</th>\n",
       "      <th>交通运输</th>\n",
       "      <th>信息软件</th>\n",
       "      <th>批发零售</th>\n",
       "      <th>住宿餐饮</th>\n",
       "      <th>金融</th>\n",
       "      <th>房地产</th>\n",
       "      <th>租赁商务</th>\n",
       "      <th>科学研究</th>\n",
       "      <th>水环公设施</th>\n",
       "      <th>居民服务</th>\n",
       "      <th>教育</th>\n",
       "      <th>卫生与社会</th>\n",
       "      <th>文体娱</th>\n",
       "      <th>公共管理</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>8917.5</td>\n",
       "      <td>7374.8</td>\n",
       "      <td>48781.1</td>\n",
       "      <td>11249.0</td>\n",
       "      <td>8299.2</td>\n",
       "      <td>22697.8</td>\n",
       "      <td>9086.7</td>\n",
       "      <td>8815.8</td>\n",
       "      <td>3436.6</td>\n",
       "      <td>5730.4</td>\n",
       "      <td>36063.2</td>\n",
       "      <td>2452.7</td>\n",
       "      <td>2134.2</td>\n",
       "      <td>1704.6</td>\n",
       "      <td>3751.0</td>\n",
       "      <td>5680.3</td>\n",
       "      <td>3408.4</td>\n",
       "      <td>1030.7</td>\n",
       "      <td>9764.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>8850.1</td>\n",
       "      <td>8703.7</td>\n",
       "      <td>57753.2</td>\n",
       "      <td>14711.2</td>\n",
       "      <td>8326.5</td>\n",
       "      <td>28170.1</td>\n",
       "      <td>10371.3</td>\n",
       "      <td>9118.2</td>\n",
       "      <td>3592.5</td>\n",
       "      <td>5357.8</td>\n",
       "      <td>45032.6</td>\n",
       "      <td>2636.2</td>\n",
       "      <td>2297.0</td>\n",
       "      <td>5888.8</td>\n",
       "      <td>3569.5</td>\n",
       "      <td>7135.7</td>\n",
       "      <td>3632.6</td>\n",
       "      <td>1525.4</td>\n",
       "      <td>11413.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>8837.1</td>\n",
       "      <td>10463.2</td>\n",
       "      <td>69060.8</td>\n",
       "      <td>19394.4</td>\n",
       "      <td>8341.2</td>\n",
       "      <td>34304.2</td>\n",
       "      <td>11283.7</td>\n",
       "      <td>9675.4</td>\n",
       "      <td>3851.8</td>\n",
       "      <td>5033.2</td>\n",
       "      <td>55673.8</td>\n",
       "      <td>2839.9</td>\n",
       "      <td>2461.6</td>\n",
       "      <td>10230.7</td>\n",
       "      <td>3451.8</td>\n",
       "      <td>8757.3</td>\n",
       "      <td>5820.5</td>\n",
       "      <td>2021.4</td>\n",
       "      <td>13093.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>8971.1</td>\n",
       "      <td>13074.4</td>\n",
       "      <td>84269.7</td>\n",
       "      <td>25091.2</td>\n",
       "      <td>8446.1</td>\n",
       "      <td>41179.0</td>\n",
       "      <td>11843.3</td>\n",
       "      <td>10576.8</td>\n",
       "      <td>4289.8</td>\n",
       "      <td>4746.1</td>\n",
       "      <td>67104.4</td>\n",
       "      <td>3103.6</td>\n",
       "      <td>2695.6</td>\n",
       "      <td>15141.9</td>\n",
       "      <td>3358.5</td>\n",
       "      <td>10323.1</td>\n",
       "      <td>6061.4</td>\n",
       "      <td>2527.1</td>\n",
       "      <td>14822.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>9297.9</td>\n",
       "      <td>16100.6</td>\n",
       "      <td>102219.3</td>\n",
       "      <td>30591.4</td>\n",
       "      <td>8666.2</td>\n",
       "      <td>49161.3</td>\n",
       "      <td>12463.3</td>\n",
       "      <td>11624.4</td>\n",
       "      <td>4903.7</td>\n",
       "      <td>4497.6</td>\n",
       "      <td>80463.6</td>\n",
       "      <td>3461.3</td>\n",
       "      <td>2932.1</td>\n",
       "      <td>20351.7</td>\n",
       "      <td>3317.1</td>\n",
       "      <td>11775.3</td>\n",
       "      <td>6351.5</td>\n",
       "      <td>3144.0</td>\n",
       "      <td>16483.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007</th>\n",
       "      <td>9857.0</td>\n",
       "      <td>19874.9</td>\n",
       "      <td>125946.2</td>\n",
       "      <td>35997.6</td>\n",
       "      <td>9023.7</td>\n",
       "      <td>57779.1</td>\n",
       "      <td>13000.5</td>\n",
       "      <td>13039.8</td>\n",
       "      <td>5793.4</td>\n",
       "      <td>4304.1</td>\n",
       "      <td>97607.1</td>\n",
       "      <td>3959.5</td>\n",
       "      <td>3191.5</td>\n",
       "      <td>26481.4</td>\n",
       "      <td>3324.4</td>\n",
       "      <td>13146.6</td>\n",
       "      <td>6699.4</td>\n",
       "      <td>3950.2</td>\n",
       "      <td>18016.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008</th>\n",
       "      <td>10958.9</td>\n",
       "      <td>24550.1</td>\n",
       "      <td>156112.4</td>\n",
       "      <td>41870.0</td>\n",
       "      <td>9495.7</td>\n",
       "      <td>67090.0</td>\n",
       "      <td>13705.7</td>\n",
       "      <td>14969.1</td>\n",
       "      <td>6948.0</td>\n",
       "      <td>4203.5</td>\n",
       "      <td>118793.1</td>\n",
       "      <td>4743.9</td>\n",
       "      <td>3589.7</td>\n",
       "      <td>34370.3</td>\n",
       "      <td>3389.7</td>\n",
       "      <td>14494.6</td>\n",
       "      <td>7212.8</td>\n",
       "      <td>4927.6</td>\n",
       "      <td>19757.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009</th>\n",
       "      <td>12666.2</td>\n",
       "      <td>29507.6</td>\n",
       "      <td>190955.6</td>\n",
       "      <td>49115.0</td>\n",
       "      <td>10206.4</td>\n",
       "      <td>80644.5</td>\n",
       "      <td>14611.2</td>\n",
       "      <td>17714.7</td>\n",
       "      <td>8419.2</td>\n",
       "      <td>4176.6</td>\n",
       "      <td>142744.1</td>\n",
       "      <td>5910.8</td>\n",
       "      <td>4206.5</td>\n",
       "      <td>45286.7</td>\n",
       "      <td>3586.9</td>\n",
       "      <td>16352.5</td>\n",
       "      <td>8176.3</td>\n",
       "      <td>6302.7</td>\n",
       "      <td>21865.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010</th>\n",
       "      <td>14572.5</td>\n",
       "      <td>34923.5</td>\n",
       "      <td>232968.9</td>\n",
       "      <td>56262.0</td>\n",
       "      <td>11352.7</td>\n",
       "      <td>96738.6</td>\n",
       "      <td>15159.1</td>\n",
       "      <td>20569.2</td>\n",
       "      <td>10166.0</td>\n",
       "      <td>4228.2</td>\n",
       "      <td>172567.7</td>\n",
       "      <td>7370.2</td>\n",
       "      <td>4852.3</td>\n",
       "      <td>58470.9</td>\n",
       "      <td>3897.9</td>\n",
       "      <td>18406.1</td>\n",
       "      <td>9228.7</td>\n",
       "      <td>7893.9</td>\n",
       "      <td>24215.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>18329.0</td>\n",
       "      <td>40837.4</td>\n",
       "      <td>288118.1</td>\n",
       "      <td>61977.3</td>\n",
       "      <td>13043.5</td>\n",
       "      <td>110332.7</td>\n",
       "      <td>15350.0</td>\n",
       "      <td>24463.9</td>\n",
       "      <td>12375.8</td>\n",
       "      <td>4382.4</td>\n",
       "      <td>211005.5</td>\n",
       "      <td>9234.9</td>\n",
       "      <td>5680.2</td>\n",
       "      <td>71955.4</td>\n",
       "      <td>4467.7</td>\n",
       "      <td>20176.0</td>\n",
       "      <td>10367.0</td>\n",
       "      <td>9593.7</td>\n",
       "      <td>26920.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>22818.2</td>\n",
       "      <td>46657.6</td>\n",
       "      <td>347329.9</td>\n",
       "      <td>67785.9</td>\n",
       "      <td>14797.6</td>\n",
       "      <td>123115.7</td>\n",
       "      <td>15768.5</td>\n",
       "      <td>29291.9</td>\n",
       "      <td>14976.3</td>\n",
       "      <td>4625.4</td>\n",
       "      <td>254101.6</td>\n",
       "      <td>11625.8</td>\n",
       "      <td>6893.2</td>\n",
       "      <td>86596.6</td>\n",
       "      <td>5296.5</td>\n",
       "      <td>22164.0</td>\n",
       "      <td>11485.7</td>\n",
       "      <td>11769.9</td>\n",
       "      <td>29427.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>28178.9</td>\n",
       "      <td>52261.5</td>\n",
       "      <td>409158.7</td>\n",
       "      <td>74060.3</td>\n",
       "      <td>16130.3</td>\n",
       "      <td>136574.0</td>\n",
       "      <td>16287.2</td>\n",
       "      <td>35106.0</td>\n",
       "      <td>17745.9</td>\n",
       "      <td>5057.8</td>\n",
       "      <td>301670.8</td>\n",
       "      <td>14391.5</td>\n",
       "      <td>8326.3</td>\n",
       "      <td>104481.0</td>\n",
       "      <td>6197.4</td>\n",
       "      <td>24267.7</td>\n",
       "      <td>12739.8</td>\n",
       "      <td>14175.4</td>\n",
       "      <td>31378.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>34431.6</td>\n",
       "      <td>56682.8</td>\n",
       "      <td>469984.4</td>\n",
       "      <td>80925.6</td>\n",
       "      <td>17513.4</td>\n",
       "      <td>151621.7</td>\n",
       "      <td>17293.4</td>\n",
       "      <td>41799.4</td>\n",
       "      <td>20222.6</td>\n",
       "      <td>5501.5</td>\n",
       "      <td>347960.9</td>\n",
       "      <td>17980.4</td>\n",
       "      <td>10173.2</td>\n",
       "      <td>124787.4</td>\n",
       "      <td>7126.5</td>\n",
       "      <td>26755.3</td>\n",
       "      <td>14252.9</td>\n",
       "      <td>16768.4</td>\n",
       "      <td>33698.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>42082.4</td>\n",
       "      <td>59376.6</td>\n",
       "      <td>526666.3</td>\n",
       "      <td>88454.8</td>\n",
       "      <td>19120.9</td>\n",
       "      <td>167211.6</td>\n",
       "      <td>18827.3</td>\n",
       "      <td>49203.4</td>\n",
       "      <td>22470.2</td>\n",
       "      <td>5836.7</td>\n",
       "      <td>388641.8</td>\n",
       "      <td>21907.0</td>\n",
       "      <td>12014.3</td>\n",
       "      <td>147147.6</td>\n",
       "      <td>8109.7</td>\n",
       "      <td>29437.8</td>\n",
       "      <td>16128.0</td>\n",
       "      <td>19302.2</td>\n",
       "      <td>35978.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>51102.8</td>\n",
       "      <td>60393.9</td>\n",
       "      <td>582266.5</td>\n",
       "      <td>96958.4</td>\n",
       "      <td>20454.5</td>\n",
       "      <td>183733.0</td>\n",
       "      <td>20642.3</td>\n",
       "      <td>55700.5</td>\n",
       "      <td>24284.7</td>\n",
       "      <td>6147.7</td>\n",
       "      <td>430450.8</td>\n",
       "      <td>27068.7</td>\n",
       "      <td>14114.2</td>\n",
       "      <td>174577.3</td>\n",
       "      <td>9043.6</td>\n",
       "      <td>32718.3</td>\n",
       "      <td>18482.9</td>\n",
       "      <td>22131.9</td>\n",
       "      <td>38277.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>61602.5</td>\n",
       "      <td>61163.7</td>\n",
       "      <td>644337.3</td>\n",
       "      <td>106025.9</td>\n",
       "      <td>21293.3</td>\n",
       "      <td>205270.0</td>\n",
       "      <td>22908.5</td>\n",
       "      <td>61659.5</td>\n",
       "      <td>26348.3</td>\n",
       "      <td>6357.6</td>\n",
       "      <td>473791.8</td>\n",
       "      <td>32710.5</td>\n",
       "      <td>16546.9</td>\n",
       "      <td>210014.0</td>\n",
       "      <td>10023.6</td>\n",
       "      <td>37178.2</td>\n",
       "      <td>21547.8</td>\n",
       "      <td>25670.3</td>\n",
       "      <td>40737.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>74638.7</td>\n",
       "      <td>62699.4</td>\n",
       "      <td>723605.7</td>\n",
       "      <td>114742.3</td>\n",
       "      <td>21968.1</td>\n",
       "      <td>230474.2</td>\n",
       "      <td>25529.5</td>\n",
       "      <td>65802.2</td>\n",
       "      <td>28387.4</td>\n",
       "      <td>6551.7</td>\n",
       "      <td>518556.3</td>\n",
       "      <td>39471.6</td>\n",
       "      <td>19503.6</td>\n",
       "      <td>249786.1</td>\n",
       "      <td>10862.3</td>\n",
       "      <td>42546.3</td>\n",
       "      <td>25166.6</td>\n",
       "      <td>30607.6</td>\n",
       "      <td>42696.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>87554.0</td>\n",
       "      <td>65865.0</td>\n",
       "      <td>804415.9</td>\n",
       "      <td>124031.1</td>\n",
       "      <td>20928.3</td>\n",
       "      <td>256623.6</td>\n",
       "      <td>28443.0</td>\n",
       "      <td>68515.7</td>\n",
       "      <td>30395.3</td>\n",
       "      <td>6748.1</td>\n",
       "      <td>568423.1</td>\n",
       "      <td>47534.4</td>\n",
       "      <td>22977.6</td>\n",
       "      <td>291676.0</td>\n",
       "      <td>11552.7</td>\n",
       "      <td>49155.7</td>\n",
       "      <td>29008.1</td>\n",
       "      <td>36268.8</td>\n",
       "      <td>43974.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020</th>\n",
       "      <td>103422.1</td>\n",
       "      <td>67864.2</td>\n",
       "      <td>875917.4</td>\n",
       "      <td>136312.4</td>\n",
       "      <td>19984.5</td>\n",
       "      <td>281385.1</td>\n",
       "      <td>31928.7</td>\n",
       "      <td>69280.3</td>\n",
       "      <td>32034.6</td>\n",
       "      <td>6759.2</td>\n",
       "      <td>618970.2</td>\n",
       "      <td>55538.4</td>\n",
       "      <td>26328.3</td>\n",
       "      <td>331103.9</td>\n",
       "      <td>12122.0</td>\n",
       "      <td>56478.1</td>\n",
       "      <td>34038.7</td>\n",
       "      <td>41720.2</td>\n",
       "      <td>44927.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021</th>\n",
       "      <td>122065.2</td>\n",
       "      <td>70586.6</td>\n",
       "      <td>969455.4</td>\n",
       "      <td>148742.7</td>\n",
       "      <td>19156.6</td>\n",
       "      <td>307251.5</td>\n",
       "      <td>36314.5</td>\n",
       "      <td>69995.4</td>\n",
       "      <td>33972.8</td>\n",
       "      <td>6842.2</td>\n",
       "      <td>675793.4</td>\n",
       "      <td>65116.3</td>\n",
       "      <td>30431.1</td>\n",
       "      <td>369742.0</td>\n",
       "      <td>12608.9</td>\n",
       "      <td>65037.1</td>\n",
       "      <td>40450.7</td>\n",
       "      <td>47407.0</td>\n",
       "      <td>44549.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>140702.3</td>\n",
       "      <td>74214.4</td>\n",
       "      <td>1075132.4</td>\n",
       "      <td>164020.9</td>\n",
       "      <td>18390.2</td>\n",
       "      <td>332161.6</td>\n",
       "      <td>40674.0</td>\n",
       "      <td>70920.5</td>\n",
       "      <td>36069.8</td>\n",
       "      <td>6933.7</td>\n",
       "      <td>718599.9</td>\n",
       "      <td>75561.9</td>\n",
       "      <td>35426.7</td>\n",
       "      <td>409597.4</td>\n",
       "      <td>13296.0</td>\n",
       "      <td>73170.7</td>\n",
       "      <td>48507.5</td>\n",
       "      <td>52980.8</td>\n",
       "      <td>45164.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>157764.6</td>\n",
       "      <td>78310.5</td>\n",
       "      <td>1188651.7</td>\n",
       "      <td>184115.3</td>\n",
       "      <td>17757.1</td>\n",
       "      <td>356895.8</td>\n",
       "      <td>45724.3</td>\n",
       "      <td>71782.7</td>\n",
       "      <td>38458.9</td>\n",
       "      <td>7077.8</td>\n",
       "      <td>750529.5</td>\n",
       "      <td>87232.0</td>\n",
       "      <td>41308.4</td>\n",
       "      <td>446022.3</td>\n",
       "      <td>14132.7</td>\n",
       "      <td>81106.3</td>\n",
       "      <td>55471.8</td>\n",
       "      <td>58311.9</td>\n",
       "      <td>44518.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024</th>\n",
       "      <td>176898.5</td>\n",
       "      <td>82504.4</td>\n",
       "      <td>1307700.5</td>\n",
       "      <td>208838.6</td>\n",
       "      <td>17166.6</td>\n",
       "      <td>381621.8</td>\n",
       "      <td>50907.3</td>\n",
       "      <td>72936.8</td>\n",
       "      <td>41948.5</td>\n",
       "      <td>7140.4</td>\n",
       "      <td>770802.9</td>\n",
       "      <td>98816.8</td>\n",
       "      <td>47543.5</td>\n",
       "      <td>480657.8</td>\n",
       "      <td>14893.0</td>\n",
       "      <td>88058.2</td>\n",
       "      <td>60610.2</td>\n",
       "      <td>63142.2</td>\n",
       "      <td>43720.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          农林牧渔       采矿         制造      电热燃水       建筑      交通运输     信息软件  \\\n",
       "2002    8917.5   7374.8    48781.1   11249.0   8299.2   22697.8   9086.7   \n",
       "2003    8850.1   8703.7    57753.2   14711.2   8326.5   28170.1  10371.3   \n",
       "2004    8837.1  10463.2    69060.8   19394.4   8341.2   34304.2  11283.7   \n",
       "2005    8971.1  13074.4    84269.7   25091.2   8446.1   41179.0  11843.3   \n",
       "2006    9297.9  16100.6   102219.3   30591.4   8666.2   49161.3  12463.3   \n",
       "2007    9857.0  19874.9   125946.2   35997.6   9023.7   57779.1  13000.5   \n",
       "2008   10958.9  24550.1   156112.4   41870.0   9495.7   67090.0  13705.7   \n",
       "2009   12666.2  29507.6   190955.6   49115.0  10206.4   80644.5  14611.2   \n",
       "2010   14572.5  34923.5   232968.9   56262.0  11352.7   96738.6  15159.1   \n",
       "2011   18329.0  40837.4   288118.1   61977.3  13043.5  110332.7  15350.0   \n",
       "2012   22818.2  46657.6   347329.9   67785.9  14797.6  123115.7  15768.5   \n",
       "2013   28178.9  52261.5   409158.7   74060.3  16130.3  136574.0  16287.2   \n",
       "2014   34431.6  56682.8   469984.4   80925.6  17513.4  151621.7  17293.4   \n",
       "2015   42082.4  59376.6   526666.3   88454.8  19120.9  167211.6  18827.3   \n",
       "2016   51102.8  60393.9   582266.5   96958.4  20454.5  183733.0  20642.3   \n",
       "2017   61602.5  61163.7   644337.3  106025.9  21293.3  205270.0  22908.5   \n",
       "2018   74638.7  62699.4   723605.7  114742.3  21968.1  230474.2  25529.5   \n",
       "2019   87554.0  65865.0   804415.9  124031.1  20928.3  256623.6  28443.0   \n",
       "2020  103422.1  67864.2   875917.4  136312.4  19984.5  281385.1  31928.7   \n",
       "2021  122065.2  70586.6   969455.4  148742.7  19156.6  307251.5  36314.5   \n",
       "2022  140702.3  74214.4  1075132.4  164020.9  18390.2  332161.6  40674.0   \n",
       "2023  157764.6  78310.5  1188651.7  184115.3  17757.1  356895.8  45724.3   \n",
       "2024  176898.5  82504.4  1307700.5  208838.6  17166.6  381621.8  50907.3   \n",
       "\n",
       "         批发零售     住宿餐饮      金融       房地产     租赁商务     科学研究     水环公设施     居民服务  \\\n",
       "2002   8815.8   3436.6  5730.4   36063.2   2452.7   2134.2    1704.6   3751.0   \n",
       "2003   9118.2   3592.5  5357.8   45032.6   2636.2   2297.0    5888.8   3569.5   \n",
       "2004   9675.4   3851.8  5033.2   55673.8   2839.9   2461.6   10230.7   3451.8   \n",
       "2005  10576.8   4289.8  4746.1   67104.4   3103.6   2695.6   15141.9   3358.5   \n",
       "2006  11624.4   4903.7  4497.6   80463.6   3461.3   2932.1   20351.7   3317.1   \n",
       "2007  13039.8   5793.4  4304.1   97607.1   3959.5   3191.5   26481.4   3324.4   \n",
       "2008  14969.1   6948.0  4203.5  118793.1   4743.9   3589.7   34370.3   3389.7   \n",
       "2009  17714.7   8419.2  4176.6  142744.1   5910.8   4206.5   45286.7   3586.9   \n",
       "2010  20569.2  10166.0  4228.2  172567.7   7370.2   4852.3   58470.9   3897.9   \n",
       "2011  24463.9  12375.8  4382.4  211005.5   9234.9   5680.2   71955.4   4467.7   \n",
       "2012  29291.9  14976.3  4625.4  254101.6  11625.8   6893.2   86596.6   5296.5   \n",
       "2013  35106.0  17745.9  5057.8  301670.8  14391.5   8326.3  104481.0   6197.4   \n",
       "2014  41799.4  20222.6  5501.5  347960.9  17980.4  10173.2  124787.4   7126.5   \n",
       "2015  49203.4  22470.2  5836.7  388641.8  21907.0  12014.3  147147.6   8109.7   \n",
       "2016  55700.5  24284.7  6147.7  430450.8  27068.7  14114.2  174577.3   9043.6   \n",
       "2017  61659.5  26348.3  6357.6  473791.8  32710.5  16546.9  210014.0  10023.6   \n",
       "2018  65802.2  28387.4  6551.7  518556.3  39471.6  19503.6  249786.1  10862.3   \n",
       "2019  68515.7  30395.3  6748.1  568423.1  47534.4  22977.6  291676.0  11552.7   \n",
       "2020  69280.3  32034.6  6759.2  618970.2  55538.4  26328.3  331103.9  12122.0   \n",
       "2021  69995.4  33972.8  6842.2  675793.4  65116.3  30431.1  369742.0  12608.9   \n",
       "2022  70920.5  36069.8  6933.7  718599.9  75561.9  35426.7  409597.4  13296.0   \n",
       "2023  71782.7  38458.9  7077.8  750529.5  87232.0  41308.4  446022.3  14132.7   \n",
       "2024  72936.8  41948.5  7140.4  770802.9  98816.8  47543.5  480657.8  14893.0   \n",
       "\n",
       "           教育    卫生与社会      文体娱     公共管理  \n",
       "2002   5680.3   3408.4   1030.7   9764.3  \n",
       "2003   7135.7   3632.6   1525.4  11413.7  \n",
       "2004   8757.3   5820.5   2021.4  13093.5  \n",
       "2005  10323.1   6061.4   2527.1  14822.4  \n",
       "2006  11775.3   6351.5   3144.0  16483.6  \n",
       "2007  13146.6   6699.4   3950.2  18016.5  \n",
       "2008  14494.6   7212.8   4927.6  19757.1  \n",
       "2009  16352.5   8176.3   6302.7  21865.8  \n",
       "2010  18406.1   9228.7   7893.9  24215.3  \n",
       "2011  20176.0  10367.0   9593.7  26920.0  \n",
       "2012  22164.0  11485.7  11769.9  29427.7  \n",
       "2013  24267.7  12739.8  14175.4  31378.7  \n",
       "2014  26755.3  14252.9  16768.4  33698.8  \n",
       "2015  29437.8  16128.0  19302.2  35978.0  \n",
       "2016  32718.3  18482.9  22131.9  38277.2  \n",
       "2017  37178.2  21547.8  25670.3  40737.7  \n",
       "2018  42546.3  25166.6  30607.6  42696.5  \n",
       "2019  49155.7  29008.1  36268.8  43974.4  \n",
       "2020  56478.1  34038.7  41720.2  44927.8  \n",
       "2021  65037.1  40450.7  47407.0  44549.3  \n",
       "2022  73170.7  48507.5  52980.8  45164.3  \n",
       "2023  81106.3  55471.8  58311.9  44518.3  \n",
       "2024  88058.2  60610.2  63142.2  43720.9  "
      ]
     },
     "execution_count": 174,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bea_all = build_df_all + equipment_df_all\n",
    "bea_all.T.round(1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "73971d37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2002     200378.3\n",
       "2003     238086.1\n",
       "2004     284595.5\n",
       "2005     337625.5\n",
       "2006     397805.9\n",
       "2007     470992.9\n",
       "2008     561182.2\n",
       "2009     672449.3\n",
       "2010     803843.7\n",
       "2011     958610.5\n",
       "2012    1126528.0\n",
       "2013    1308189.2\n",
       "2014    1495480.2\n",
       "2015    1677916.6\n",
       "2016    1868549.2\n",
       "2017    2085187.4\n",
       "2018    2333596.1\n",
       "2019    2594090.8\n",
       "2020    2846116.1\n",
       "2021    3135518.7\n",
       "2022    3431525.0\n",
       "2023    3725171.9\n",
       "2024    4015908.9\n",
       "dtype: float64"
      ]
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bea = bea_all.T.round(1)\n",
    "bea.sum(axis=1)\n"
   ]
  }
 ],
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